Cure Model Regression
cureit.RdCure Model Regression
Usage
# S3 method for formula
cureit(
surv_formula,
cure_formula,
data,
conf.level = 0.95,
nboot = 100,
eps = 1e-07,
...
)
cureit(object, ...)
# S3 method for default
cureit(object, ...)Arguments
- surv_formula
formula with
Surv()on LHS and covariates on RHS.- cure_formula
formula with covariates for cure fraction on RHS
- data
data frame
- conf.level
confidence level. Default is 0.95.
- nboot
number of bootstrap samples used for inference.
- eps
convergence criterion for the EM algorithm.
- ...
passed to methods
- object
input object
See also
Other cureit() functions:
Brier_inference_bootstrap(),
broom_methods_cureit,
nomogram(),
predict.cureit()
Examples
cureit(surv_formula = Surv(ttdeath, death) ~ age + grade,
cure_formula = ~ age + grade, data = trial)
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002616112 0.569504769 0.345883977
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.575003030 0.009813492 0.108542405
#> grade_iii, Cure model
#> 0.823899189
#>
#> $surv_formula
#> Surv(ttdeath, death) ~ age + grade
#> <environment: 0x55c025b65418>
#>
#> $cure_formula
#> ~age + grade
#> <environment: 0x55c025b65418>
#>
#> $data
#> # A tibble: 200 × 8
#> trt age marker stage grade response death ttdeath
#> <chr> <dbl> <dbl> <fct> <fct> <int> <dbl> <dbl>
#> 1 Drug A 23 0.16 T1 II 0 0 24
#> 2 Drug B 9 1.11 T2 I 1 0 24
#> 3 Drug A 31 0.277 T1 II 0 0 24
#> 4 Drug A NA 2.07 T3 III 1 1 17.6
#> 5 Drug A 51 2.77 T4 III 1 1 16.4
#> 6 Drug B 39 0.613 T4 I 0 1 15.6
#> 7 Drug A 37 0.354 T1 II 0 0 24
#> 8 Drug A 32 1.74 T1 I 0 1 18.4
#> 9 Drug A 31 0.144 T1 II 0 0 24
#> 10 Drug B 34 0.205 T3 I 0 1 10.5
#> # … with 190 more rows
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> $surv_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $cure_xlevels
#> $cure_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 7
#> term estimate std.error statistic conf.low conf.h…¹ p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.575 0.486 -1.18 -1.53 0.379 0.237
#> 2 age, Cure model 0.00981 0.00982 0.999 -0.00944 0.0291 0.318
#> 3 grade_ii, Cure model 0.109 0.329 0.330 -0.537 0.754 0.742
#> 4 grade_iii, Cure model 0.824 0.385 2.14 0.0691 1.58 0.0324
#> # … with abbreviated variable name ¹conf.high
#>
#> $tidy$df_surv
#> # A tibble: 3 × 7
#> term estimate std.error statistic conf.…¹ conf.…² p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00262 0.00907 -0.288 -0.0204 0.0152 0.773
#> 2 grade_ii, Survival model 0.570 0.272 2.09 0.0359 1.10 0.0364
#> 3 grade_iii, Survival model 0.346 0.272 1.27 -0.186 0.878 0.203
#> # … with abbreviated variable names ¹conf.low, ²conf.high
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003 0.009813 0.108542 0.823899
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 253.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003030 0.009813492 0.108542405 0.823899189
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002616112 0.569504769 0.345883977
#>
#> $b_var
#> [1] 2.366736e-01 9.650257e-05 1.083741e-01 1.483008e-01
#>
#> $b_sd
#> [1] 0.486491144 0.009823572 0.329202274 0.385098463
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.1819394 0.9989739 0.3297134 2.1394507
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.23722976 0.31780732 0.74161652 0.03239918
#>
#> $beta_var
#> [1] 8.227479e-05 7.411046e-02 7.375836e-02
#>
#> $beta_sd
#> [1] 0.009070545 0.272232361 0.271584913
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.2884184 2.0919804 1.2735758
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.77302650 0.03644027 0.20281379
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.000000000 0.000000000 0.000000000 0.604678067 0.658063410 0.000000000
#> [7] 0.417229340 0.000000000 0.879376354 0.000000000 0.000000000 0.744886187
#> [13] 0.787600867 0.142672058 0.944518547 0.000000000 0.693100768 0.000000000
#> [19] 0.000000000 0.000000000 0.000000000 0.540871173 0.006912639 0.976381134
#> [25] 0.640373656 0.000000000 0.000000000 0.684419417 0.522291631 0.000000000
#> [31] 0.278243702 0.000000000 0.000000000 0.000000000 0.246976530 0.821307758
#> [37] 0.000000000 0.666890646 0.466018936 0.456394953 0.829660071 0.854634203
#> [43] 0.000000000 0.531599829 0.000000000 0.000000000 0.000000000 0.846335953
#> [49] 0.446649365 0.887603756 0.000000000 0.000000000 0.368370905 0.837991986
#> [55] 0.736284601 0.368370905 0.762052697 0.904005497 0.000000000 0.130947018
#> [61] 0.000000000 0.000000000 0.178167087 0.000000000 0.298558895 0.093531067
#> [67] 0.960518552 0.000000000 0.000000000 0.000000000 0.000000000 0.387858887
#> [73] 0.968455884 0.020860827 0.613665875 0.000000000 0.753465281 0.000000000
#> [79] 0.000000000 0.000000000 0.586773524 0.036370054 0.000000000 0.427038837
#> [85] 0.267747949 0.984266892 0.106209363 0.895813391 0.000000000 0.000000000
#> [91] 0.727657186 0.397671772 0.000000000 0.246976530 0.631469660 0.920311545
#> [97] 0.000000000 0.000000000 0.000000000 0.348502061 0.550166021 0.862915985
#> [103] 0.436874482 0.000000000 0.494318881 0.513013956 0.000000000 0.118522726
#> [109] 0.000000000 0.503694197 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.779118376 0.649247645 0.000000000 0.992139734 0.308649170
#> [121] 0.080274841 0.568542449 0.000000000 0.000000000 0.718999352 0.475516896
#> [127] 0.000000000 0.201867710 0.000000000 0.000000000 0.224987874 0.796088245
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.912176411 0.000000000
#> [139] 0.000000000 0.000000000 0.952539418 0.318644852 0.000000000 0.000000000
#> [145] 0.236117909 0.804529313 0.770582430 0.000000000 0.701722215 0.328677697
#> [151] 0.871155498 0.000000000 0.000000000 0.000000000 0.000000000 0.065734870
#> [157] 0.000000000 0.338572747 0.675684959 0.050684149 0.154512416 0.358472658
#> [163] 0.559374570 0.000000000 0.000000000 0.000000000 0.189977968 0.000000000
#> [169] 0.812910823 0.000000000 0.407438340 0.710355937 0.577676416 0.000000000
#> [175] 0.936485829 0.484909262 0.000000000 0.000000000 0.928419678 0.622583868
#> [181] 0.288505592 0.000000000 0.586773524 0.000000000 0.166456957 0.000000000
#> [187] 0.213576414 0.000000000 0.000000000
#>
#> $Time
#> 1 2 3 5 6 7 8 9 10 11 12 13 14
#> 24.00 24.00 24.00 16.43 15.64 24.00 18.43 24.00 10.53 24.00 24.00 14.34 12.89
#> 15 16 17 18 19 20 21 22 23 24 25 26 27
#> 22.68 8.71 24.00 15.21 24.00 24.00 24.00 24.00 16.92 23.89 6.32 15.77 24.00
#> 28 29 30 31 32 33 34 35 36 37 38 39 40
#> 24.00 15.45 17.43 24.00 20.90 24.00 24.00 24.00 21.19 12.52 24.00 15.59 18.00
#> 41 42 43 44 45 46 47 48 49 51 52 53 54
#> 18.02 12.43 12.10 24.00 17.42 24.00 24.00 24.00 12.19 18.23 10.42 24.00 24.00
#> 55 56 57 58 60 61 62 63 64 65 66 67 68
#> 19.34 12.21 14.46 19.34 13.15 10.12 24.00 22.77 24.00 24.00 22.13 24.00 20.62
#> 69 70 71 72 74 75 76 77 78 79 80 81 82
#> 23.23 7.38 24.00 24.00 24.00 24.00 19.22 7.27 23.88 16.23 24.00 14.06 24.00
#> 83 84 85 86 87 88 90 91 92 93 94 95 96
#> 24.00 24.00 16.44 23.81 24.00 18.37 20.94 5.33 22.92 10.33 24.00 24.00 14.54
#> 97 98 99 100 101 102 103 104 105 106 107 108 109
#> 19.14 24.00 21.19 16.07 9.97 24.00 24.00 24.00 19.75 16.67 11.18 18.29 24.00
#> 110 111 112 113 116 117 118 119 120 121 122 123 125
#> 17.56 17.45 24.00 22.86 24.00 17.46 24.00 24.00 24.00 24.00 24.00 13.00 15.65
#> 126 127 128 129 130 131 132 133 134 135 136 137 138
#> 24.00 3.53 20.35 23.41 16.47 24.00 24.00 14.65 17.81 24.00 21.83 24.00 24.00
#> 139 140 141 142 143 144 145 146 147 148 149 150 151
#> 21.49 12.68 24.00 24.00 24.00 24.00 10.07 24.00 24.00 24.00 8.37 20.33 24.00
#> 152 153 154 155 156 157 158 159 160 161 162 163 164
#> 24.00 21.33 12.63 13.08 24.00 15.10 20.14 10.55 24.00 24.00 24.00 24.00 23.60
#> 165 166 167 168 169 170 171 172 173 174 175 176 177
#> 24.00 19.98 15.55 23.72 22.41 19.54 16.57 24.00 24.00 24.00 21.91 24.00 12.53
#> 178 179 180 181 182 183 184 185 186 187 188 190 191
#> 24.00 18.63 14.82 16.46 24.00 9.24 17.77 24.00 24.00 9.92 16.16 20.81 24.00
#> 192 193 194 196 197 198 200
#> 16.44 24.00 22.40 24.00 21.60 24.00 24.00
#>
#> $bootstrap_fit
#> $bootstrap_fit[[1]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0004459358 0.8719428415 0.7822113181
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.70013121 0.01775052 -0.30675786
#> grade_iii, Cure model
#> 0.45172799
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 45 17.42 1 54 0 1
#> 192 16.44 1 31 1 0
#> 177 12.53 1 75 0 0
#> 93 10.33 1 52 0 1
#> 140 12.68 1 59 1 0
#> 123 13.00 1 44 1 0
#> 4 17.64 1 NA 0 1
#> 199 19.81 1 NA 0 1
#> 76 19.22 1 54 0 1
#> 13 14.34 1 54 0 1
#> 32 20.90 1 37 1 0
#> 154 12.63 1 20 1 0
#> 155 13.08 1 26 0 0
#> 145 10.07 1 65 1 0
#> 107 11.18 1 54 1 0
#> 15 22.68 1 48 0 0
#> 117 17.46 1 26 0 1
#> 123.1 13.00 1 44 1 0
#> 15.1 22.68 1 48 0 0
#> 43 12.10 1 61 0 1
#> 51 18.23 1 83 0 1
#> 43.1 12.10 1 61 0 1
#> 111 17.45 1 47 0 1
#> 81 14.06 1 34 0 0
#> 130 16.47 1 53 0 1
#> 88 18.37 1 47 0 0
#> 66 22.13 1 53 0 0
#> 10 10.53 1 34 0 0
#> 159 10.55 1 50 0 1
#> 57 14.46 1 45 0 1
#> 90 20.94 1 50 0 1
#> 91 5.33 1 61 0 1
#> 166 19.98 1 48 0 0
#> 150 20.33 1 48 0 0
#> 13.1 14.34 1 54 0 1
#> 171 16.57 1 41 0 1
#> 88.1 18.37 1 47 0 0
#> 157 15.10 1 47 0 0
#> 51.1 18.23 1 83 0 1
#> 158 20.14 1 74 1 0
#> 177.1 12.53 1 75 0 0
#> 107.1 11.18 1 54 1 0
#> 183 9.24 1 67 1 0
#> 78 23.88 1 43 0 0
#> 32.1 20.90 1 37 1 0
#> 26 15.77 1 49 0 1
#> 70 7.38 1 30 1 0
#> 52 10.42 1 52 0 1
#> 77 7.27 1 67 0 1
#> 187 9.92 1 39 1 0
#> 197 21.60 1 69 1 0
#> 167 15.55 1 56 1 0
#> 86 23.81 1 58 0 1
#> 97 19.14 1 65 0 1
#> 58 19.34 1 39 0 0
#> 43.2 12.10 1 61 0 1
#> 58.1 19.34 1 39 0 0
#> 184 17.77 1 38 0 0
#> 37 12.52 1 57 1 0
#> 93.1 10.33 1 52 0 1
#> 169 22.41 1 46 0 0
#> 99 21.19 1 38 0 1
#> 51.2 18.23 1 83 0 1
#> 69 23.23 1 25 0 1
#> 106 16.67 1 49 1 0
#> 61 10.12 1 36 0 1
#> 13.2 14.34 1 54 0 1
#> 181 16.46 1 45 0 1
#> 79 16.23 1 54 1 0
#> 61.1 10.12 1 36 0 1
#> 4.1 17.64 1 NA 0 1
#> 10.1 10.53 1 34 0 0
#> 51.3 18.23 1 83 0 1
#> 97.1 19.14 1 65 0 1
#> 123.2 13.00 1 44 1 0
#> 61.2 10.12 1 36 0 1
#> 93.2 10.33 1 52 0 1
#> 183.1 9.24 1 67 1 0
#> 8 18.43 1 32 0 0
#> 130.1 16.47 1 53 0 1
#> 58.2 19.34 1 39 0 0
#> 171.1 16.57 1 41 0 1
#> 24 23.89 1 38 0 0
#> 169.1 22.41 1 46 0 0
#> 108 18.29 1 39 0 1
#> 175 21.91 1 43 0 0
#> 192.1 16.44 1 31 1 0
#> 23 16.92 1 61 0 0
#> 36 21.19 1 48 0 1
#> 89 11.44 1 NA 0 0
#> 188 16.16 1 46 0 1
#> 18 15.21 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 61.3 10.12 1 36 0 1
#> 50 10.02 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 56 12.21 1 60 0 0
#> 110 17.56 1 65 0 1
#> 43.3 12.10 1 61 0 1
#> 63 22.77 1 31 1 0
#> 139 21.49 1 63 1 0
#> 101 9.97 1 10 0 1
#> 58.3 19.34 1 39 0 0
#> 153 21.33 1 55 1 0
#> 18.1 15.21 1 49 1 0
#> 78.1 23.88 1 43 0 0
#> 89.1 11.44 1 NA 0 0
#> 25 6.32 1 34 1 0
#> 97.2 19.14 1 65 0 1
#> 70.1 7.38 1 30 1 0
#> 55 19.34 1 69 0 1
#> 119 24.00 0 17 0 0
#> 94 24.00 0 51 0 1
#> 109 24.00 0 48 0 0
#> 46 24.00 0 71 0 0
#> 17 24.00 0 38 0 1
#> 47 24.00 0 38 0 1
#> 95 24.00 0 68 0 1
#> 7 24.00 0 37 1 0
#> 22 24.00 0 52 1 0
#> 138 24.00 0 44 1 0
#> 22.1 24.00 0 52 1 0
#> 22.2 24.00 0 52 1 0
#> 147 24.00 0 76 1 0
#> 138.1 24.00 0 44 1 0
#> 95.1 24.00 0 68 0 1
#> 182 24.00 0 35 0 0
#> 74 24.00 0 43 0 1
#> 67 24.00 0 25 0 0
#> 146 24.00 0 63 1 0
#> 17.1 24.00 0 38 0 1
#> 185 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 94.1 24.00 0 51 0 1
#> 198 24.00 0 66 0 1
#> 87 24.00 0 27 0 0
#> 152 24.00 0 36 0 1
#> 109.1 24.00 0 48 0 0
#> 82 24.00 0 34 0 0
#> 54 24.00 0 53 1 0
#> 102 24.00 0 49 0 0
#> 118 24.00 0 44 1 0
#> 87.1 24.00 0 27 0 0
#> 151 24.00 0 42 0 0
#> 19 24.00 0 57 0 1
#> 118.1 24.00 0 44 1 0
#> 67.1 24.00 0 25 0 0
#> 73 24.00 0 NA 0 1
#> 172 24.00 0 41 0 0
#> 176 24.00 0 43 0 1
#> 3 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 22.3 24.00 0 52 1 0
#> 22.4 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 53 24.00 0 32 0 1
#> 2 24.00 0 9 0 0
#> 84 24.00 0 39 0 1
#> 17.2 24.00 0 38 0 1
#> 178 24.00 0 52 1 0
#> 2.1 24.00 0 9 0 0
#> 142 24.00 0 53 0 0
#> 118.2 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 138.2 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 120 24.00 0 68 0 1
#> 2.2 24.00 0 9 0 0
#> 135.1 24.00 0 58 1 0
#> 104 24.00 0 50 1 0
#> 104.1 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 115 24.00 0 NA 1 0
#> 151.1 24.00 0 42 0 0
#> 102.1 24.00 0 49 0 0
#> 54.1 24.00 0 53 1 0
#> 161 24.00 0 45 0 0
#> 156 24.00 0 50 1 0
#> 120.1 24.00 0 68 0 1
#> 176.1 24.00 0 43 0 1
#> 120.2 24.00 0 68 0 1
#> 104.2 24.00 0 50 1 0
#> 147.1 24.00 0 76 1 0
#> 2.3 24.00 0 9 0 0
#> 27 24.00 0 63 1 0
#> 161.1 24.00 0 45 0 0
#> 144 24.00 0 28 0 1
#> 178.1 24.00 0 52 1 0
#> 94.2 24.00 0 51 0 1
#> 3.1 24.00 0 31 1 0
#> 65.1 24.00 0 57 1 0
#> 47.1 24.00 0 38 0 1
#> 121 24.00 0 57 1 0
#> 109.2 24.00 0 48 0 0
#> 22.5 24.00 0 52 1 0
#> 122 24.00 0 66 0 0
#> 19.1 24.00 0 57 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.700 NA NA NA
#> 2 age, Cure model 0.0178 NA NA NA
#> 3 grade_ii, Cure model -0.307 NA NA NA
#> 4 grade_iii, Cure model 0.452 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000446 NA NA NA
#> 2 grade_ii, Survival model 0.872 NA NA NA
#> 3 grade_iii, Survival model 0.782 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.70013 0.01775 -0.30676 0.45173
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 254.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.70013121 0.01775052 -0.30675786 0.45172799
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0004459358 0.8719428415 0.7822113181
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.61955981 0.68278194 0.82886876 0.91036148 0.81663639 0.79814925
#> [7] 0.47343680 0.76625105 0.36653952 0.82278373 0.79173735 0.94826598
#> [13] 0.87619837 0.17937218 0.60264532 0.79814925 0.17937218 0.85306021
#> [19] 0.55072158 0.85306021 0.61116932 0.78532604 0.65991126 0.52202121
#> [25] 0.24728991 0.89334021 0.88764185 0.75965131 0.35406357 0.99496752
#> [31] 0.41146195 0.38903242 0.76625105 0.64421484 0.52202121 0.75298537
#> [37] 0.55072158 0.40045342 0.82886876 0.87619837 0.96420908 0.05861601
#> [43] 0.36653952 0.71186995 0.97458329 0.90470275 0.98480949 0.95893274
#> [49] 0.28265021 0.72596955 0.11559308 0.48383277 0.42247674 0.85306021
#> [55] 0.42247674 0.58516820 0.84100000 0.91036148 0.21327050 0.32854657
#> [61] 0.55072158 0.14076524 0.63608983 0.92688445 0.76625105 0.67519501
#> [67] 0.69743162 0.92688445 0.89334021 0.55072158 0.48383277 0.79814925
#> [73] 0.92688445 0.91036148 0.96420908 0.51233577 0.65991126 0.42247674
#> [79] 0.64421484 0.02119823 0.21327050 0.54122712 0.26495864 0.68278194
#> [85] 0.62782336 0.32854657 0.70469301 0.73971494 0.71896541 0.92688445
#> [91] 0.73288479 0.84702954 0.59397899 0.85306021 0.16162162 0.29899316
#> [97] 0.95361691 0.42247674 0.31423261 0.73971494 0.05861601 0.98990617
#> [103] 0.48383277 0.97458329 0.42247674 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 45 192 177 93 140 123 76 13 32 154 155 145 107
#> 17.42 16.44 12.53 10.33 12.68 13.00 19.22 14.34 20.90 12.63 13.08 10.07 11.18
#> 15 117 123.1 15.1 43 51 43.1 111 81 130 88 66 10
#> 22.68 17.46 13.00 22.68 12.10 18.23 12.10 17.45 14.06 16.47 18.37 22.13 10.53
#> 159 57 90 91 166 150 13.1 171 88.1 157 51.1 158 177.1
#> 10.55 14.46 20.94 5.33 19.98 20.33 14.34 16.57 18.37 15.10 18.23 20.14 12.53
#> 107.1 183 78 32.1 26 70 52 77 187 197 167 86 97
#> 11.18 9.24 23.88 20.90 15.77 7.38 10.42 7.27 9.92 21.60 15.55 23.81 19.14
#> 58 43.2 58.1 184 37 93.1 169 99 51.2 69 106 61 13.2
#> 19.34 12.10 19.34 17.77 12.52 10.33 22.41 21.19 18.23 23.23 16.67 10.12 14.34
#> 181 79 61.1 10.1 51.3 97.1 123.2 61.2 93.2 183.1 8 130.1 58.2
#> 16.46 16.23 10.12 10.53 18.23 19.14 13.00 10.12 10.33 9.24 18.43 16.47 19.34
#> 171.1 24 169.1 108 175 192.1 23 36 188 18 125 61.3 29
#> 16.57 23.89 22.41 18.29 21.91 16.44 16.92 21.19 16.16 15.21 15.65 10.12 15.45
#> 56 110 43.3 63 139 101 58.3 153 18.1 78.1 25 97.2 70.1
#> 12.21 17.56 12.10 22.77 21.49 9.97 19.34 21.33 15.21 23.88 6.32 19.14 7.38
#> 55 119 94 109 46 17 47 95 7 22 138 22.1 22.2
#> 19.34 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 138.1 95.1 182 74 67 146 17.1 185 72 94.1 198 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 109.1 82 54 102 118 87.1 151 19 118.1 67.1 172 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 98 22.3 22.4 71 48 34 53 2 84 17.2 178 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 118.2 33 138.2 135 120 2.2 135.1 104 104.1 65 151.1 102.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.1 161 156 120.1 176.1 120.2 104.2 147.1 2.3 27 161.1 144 178.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.2 3.1 65.1 47.1 121 109.2 22.5 122 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[2]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0005006481 0.4034411334 0.2653423896
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.44248653 0.02698917 -0.33722960
#> grade_iii, Cure model
#> 1.19100379
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 157 15.10 1 47 0 0
#> 63 22.77 1 31 1 0
#> 37 12.52 1 57 1 0
#> 171 16.57 1 41 0 1
#> 159 10.55 1 50 0 1
#> 96 14.54 1 33 0 1
#> 41 18.02 1 40 1 0
#> 96.1 14.54 1 33 0 1
#> 108 18.29 1 39 0 1
#> 177 12.53 1 75 0 0
#> 15 22.68 1 48 0 0
#> 127 3.53 1 62 0 1
#> 91 5.33 1 61 0 1
#> 51 18.23 1 83 0 1
#> 69 23.23 1 25 0 1
#> 13 14.34 1 54 0 1
#> 51.1 18.23 1 83 0 1
#> 197 21.60 1 69 1 0
#> 61 10.12 1 36 0 1
#> 105 19.75 1 60 0 0
#> 117 17.46 1 26 0 1
#> 166 19.98 1 48 0 0
#> 51.2 18.23 1 83 0 1
#> 18 15.21 1 49 1 0
#> 25 6.32 1 34 1 0
#> 61.1 10.12 1 36 0 1
#> 8 18.43 1 32 0 0
#> 24 23.89 1 38 0 0
#> 61.2 10.12 1 36 0 1
#> 197.1 21.60 1 69 1 0
#> 61.3 10.12 1 36 0 1
#> 130 16.47 1 53 0 1
#> 30 17.43 1 78 0 0
#> 89 11.44 1 NA 0 0
#> 179 18.63 1 42 0 0
#> 108.1 18.29 1 39 0 1
#> 61.4 10.12 1 36 0 1
#> 188 16.16 1 46 0 1
#> 36 21.19 1 48 0 1
#> 81 14.06 1 34 0 0
#> 58 19.34 1 39 0 0
#> 194 22.40 1 38 0 1
#> 90 20.94 1 50 0 1
#> 42 12.43 1 49 0 1
#> 177.1 12.53 1 75 0 0
#> 18.1 15.21 1 49 1 0
#> 86 23.81 1 58 0 1
#> 26 15.77 1 49 0 1
#> 150 20.33 1 48 0 0
#> 10 10.53 1 34 0 0
#> 100 16.07 1 60 0 0
#> 25.1 6.32 1 34 1 0
#> 55 19.34 1 69 0 1
#> 89.1 11.44 1 NA 0 0
#> 106 16.67 1 49 1 0
#> 18.2 15.21 1 49 1 0
#> 164 23.60 1 76 0 1
#> 127.1 3.53 1 62 0 1
#> 6 15.64 1 39 0 0
#> 199 19.81 1 NA 0 1
#> 106.1 16.67 1 49 1 0
#> 79 16.23 1 54 1 0
#> 177.2 12.53 1 75 0 0
#> 45 17.42 1 54 0 1
#> 51.3 18.23 1 83 0 1
#> 92 22.92 1 47 0 1
#> 16 8.71 1 71 0 1
#> 154 12.63 1 20 1 0
#> 59 10.16 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 79.1 16.23 1 54 1 0
#> 23 16.92 1 61 0 0
#> 50 10.02 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 4 17.64 1 NA 0 1
#> 187 9.92 1 39 1 0
#> 170 19.54 1 43 0 1
#> 61.5 10.12 1 36 0 1
#> 125 15.65 1 67 1 0
#> 45.1 17.42 1 54 0 1
#> 45.2 17.42 1 54 0 1
#> 107 11.18 1 54 1 0
#> 92.1 22.92 1 47 0 1
#> 195 11.76 1 NA 1 0
#> 127.2 3.53 1 62 0 1
#> 66 22.13 1 53 0 0
#> 183 9.24 1 67 1 0
#> 155 13.08 1 26 0 0
#> 159.1 10.55 1 50 0 1
#> 52 10.42 1 52 0 1
#> 177.3 12.53 1 75 0 0
#> 57 14.46 1 45 0 1
#> 13.1 14.34 1 54 0 1
#> 150.1 20.33 1 48 0 0
#> 127.3 3.53 1 62 0 1
#> 77 7.27 1 67 0 1
#> 10.1 10.53 1 34 0 0
#> 59.1 10.16 1 NA 1 0
#> 69.1 23.23 1 25 0 1
#> 88 18.37 1 47 0 0
#> 77.1 7.27 1 67 0 1
#> 89.2 11.44 1 NA 0 0
#> 36.1 21.19 1 48 0 1
#> 59.2 10.16 1 NA 1 0
#> 61.6 10.12 1 36 0 1
#> 197.2 21.60 1 69 1 0
#> 77.2 7.27 1 67 0 1
#> 40 18.00 1 28 1 0
#> 14 12.89 1 21 0 0
#> 188.1 16.16 1 46 0 1
#> 5 16.43 1 51 0 1
#> 168 23.72 1 70 0 0
#> 144 24.00 0 28 0 1
#> 82 24.00 0 34 0 0
#> 67 24.00 0 25 0 0
#> 87 24.00 0 27 0 0
#> 82.1 24.00 0 34 0 0
#> 126 24.00 0 48 0 0
#> 131 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 173 24.00 0 19 0 1
#> 104.1 24.00 0 50 1 0
#> 22 24.00 0 52 1 0
#> 115 24.00 0 NA 1 0
#> 142 24.00 0 53 0 0
#> 74 24.00 0 43 0 1
#> 21 24.00 0 47 0 0
#> 83 24.00 0 6 0 0
#> 83.1 24.00 0 6 0 0
#> 193 24.00 0 45 0 1
#> 131.1 24.00 0 66 0 0
#> 74.1 24.00 0 43 0 1
#> 83.2 24.00 0 6 0 0
#> 138 24.00 0 44 1 0
#> 126.1 24.00 0 48 0 0
#> 173.1 24.00 0 19 0 1
#> 73 24.00 0 NA 0 1
#> 72 24.00 0 40 0 1
#> 146 24.00 0 63 1 0
#> 161 24.00 0 45 0 0
#> 109 24.00 0 48 0 0
#> 119 24.00 0 17 0 0
#> 131.2 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 28 24.00 0 67 1 0
#> 33 24.00 0 53 0 0
#> 83.3 24.00 0 6 0 0
#> 94 24.00 0 51 0 1
#> 137 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 80 24.00 0 41 0 0
#> 9 24.00 0 31 1 0
#> 104.2 24.00 0 50 1 0
#> 144.1 24.00 0 28 0 1
#> 186 24.00 0 45 1 0
#> 147 24.00 0 76 1 0
#> 65 24.00 0 57 1 0
#> 38 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 104.3 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 103.1 24.00 0 56 1 0
#> 182 24.00 0 35 0 0
#> 165 24.00 0 47 0 0
#> 7 24.00 0 37 1 0
#> 178 24.00 0 52 1 0
#> 138.1 24.00 0 44 1 0
#> 38.1 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 176 24.00 0 43 0 1
#> 34.1 24.00 0 36 0 0
#> 163 24.00 0 66 0 0
#> 72.1 24.00 0 40 0 1
#> 27 24.00 0 63 1 0
#> 131.3 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#> 20 24.00 0 46 1 0
#> 19.1 24.00 0 57 0 1
#> 176.1 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 193.1 24.00 0 45 0 1
#> 148 24.00 0 61 1 0
#> 132 24.00 0 55 0 0
#> 31 24.00 0 36 0 1
#> 28.1 24.00 0 67 1 0
#> 176.2 24.00 0 43 0 1
#> 33.1 24.00 0 53 0 0
#> 116 24.00 0 58 0 1
#> 162 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 3 24.00 0 31 1 0
#> 19.2 24.00 0 57 0 1
#> 54 24.00 0 53 1 0
#> 186.1 24.00 0 45 1 0
#> 9.1 24.00 0 31 1 0
#> 148.1 24.00 0 61 1 0
#> 28.2 24.00 0 67 1 0
#> 161.1 24.00 0 45 0 0
#> 137.1 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.44 NA NA NA
#> 2 age, Cure model 0.0270 NA NA NA
#> 3 grade_ii, Cure model -0.337 NA NA NA
#> 4 grade_iii, Cure model 1.19 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000501 NA NA NA
#> 2 grade_ii, Survival model 0.403 NA NA NA
#> 3 grade_iii, Survival model 0.265 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.44249 0.02699 -0.33723 1.19100
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 232 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.44248653 0.02698917 -0.33722960 1.19100379
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0005006481 0.4034411334 0.2653423896
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.65024000 0.13448317 0.77120420 0.51382852 0.79691187 0.65908171
#> [7] 0.41668532 0.65908171 0.35662411 0.73720375 0.14720345 0.96847247
#> [13] 0.96042247 0.37737470 0.08218479 0.68525781 0.37737470 0.18491498
#> [19] 0.83913009 0.28181322 0.43673435 0.27092489 0.37737470 0.62408208
#> [25] 0.94435445 0.83913009 0.33521825 0.01113250 0.83913009 0.18491498
#> [31] 0.83913009 0.52333755 0.44663795 0.32452464 0.35662411 0.83913009
#> [37] 0.56976544 0.21721860 0.70251362 0.30350402 0.15995055 0.23873159
#> [43] 0.77980473 0.73720375 0.62408208 0.03084810 0.59696476 0.24960586
#> [49] 0.81378762 0.58784845 0.94435445 0.30350402 0.49489015 0.62408208
#> [55] 0.06570534 0.96847247 0.61506142 0.49489015 0.55152376 0.73720375
#> [61] 0.45654998 0.37737470 0.10917020 0.91196934 0.72856755 0.55152376
#> [67] 0.48515536 0.53280020 0.89551254 0.29271407 0.83913009 0.60604332
#> [73] 0.45654998 0.45654998 0.78837951 0.10917020 0.96847247 0.17242074
#> [79] 0.90375771 0.71119698 0.79691187 0.83066929 0.73720375 0.67651529
#> [85] 0.68525781 0.24960586 0.96847247 0.92016192 0.81378762 0.08218479
#> [91] 0.34591732 0.92016192 0.21721860 0.83913009 0.18491498 0.92016192
#> [97] 0.42676588 0.71988171 0.56976544 0.54218388 0.04813317 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 157 63 37 171 159 96 41 96.1 108 177 15 127 91
#> 15.10 22.77 12.52 16.57 10.55 14.54 18.02 14.54 18.29 12.53 22.68 3.53 5.33
#> 51 69 13 51.1 197 61 105 117 166 51.2 18 25 61.1
#> 18.23 23.23 14.34 18.23 21.60 10.12 19.75 17.46 19.98 18.23 15.21 6.32 10.12
#> 8 24 61.2 197.1 61.3 130 30 179 108.1 61.4 188 36 81
#> 18.43 23.89 10.12 21.60 10.12 16.47 17.43 18.63 18.29 10.12 16.16 21.19 14.06
#> 58 194 90 42 177.1 18.1 86 26 150 10 100 25.1 55
#> 19.34 22.40 20.94 12.43 12.53 15.21 23.81 15.77 20.33 10.53 16.07 6.32 19.34
#> 106 18.2 164 127.1 6 106.1 79 177.2 45 51.3 92 16 154
#> 16.67 15.21 23.60 3.53 15.64 16.67 16.23 12.53 17.42 18.23 22.92 8.71 12.63
#> 79.1 23 192 187 170 61.5 125 45.1 45.2 107 92.1 127.2 66
#> 16.23 16.92 16.44 9.92 19.54 10.12 15.65 17.42 17.42 11.18 22.92 3.53 22.13
#> 183 155 159.1 52 177.3 57 13.1 150.1 127.3 77 10.1 69.1 88
#> 9.24 13.08 10.55 10.42 12.53 14.46 14.34 20.33 3.53 7.27 10.53 23.23 18.37
#> 77.1 36.1 61.6 197.2 77.2 40 14 188.1 5 168 144 82 67
#> 7.27 21.19 10.12 21.60 7.27 18.00 12.89 16.16 16.43 23.72 24.00 24.00 24.00
#> 87 82.1 126 131 104 173 104.1 22 142 74 21 83 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 131.1 74.1 83.2 138 126.1 173.1 72 146 161 109 119 131.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 28 33 83.3 94 137 75 80 9 104.2 144.1 186 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 38 48 104.3 160 19 103.1 182 165 7 178 138.1 38.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 176 34.1 163 72.1 27 131.3 200 20 19.1 176.1 185 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 132 31 28.1 176.2 33.1 116 162 196 3 19.2 54 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 148.1 28.2 161.1 137.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[3]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007398286 0.461248359 0.381295921
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.947775743 0.005047866 1.007632405
#> grade_iii, Cure model
#> 1.613859904
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 37 12.52 1 57 1 0
#> 50 10.02 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 128 20.35 1 35 0 1
#> 77 7.27 1 67 0 1
#> 190 20.81 1 42 1 0
#> 26 15.77 1 49 0 1
#> 114 13.68 1 NA 0 0
#> 26.1 15.77 1 49 0 1
#> 97 19.14 1 65 0 1
#> 18 15.21 1 49 1 0
#> 25 6.32 1 34 1 0
#> 153 21.33 1 55 1 0
#> 111 17.45 1 47 0 1
#> 107 11.18 1 54 1 0
#> 13 14.34 1 54 0 1
#> 183 9.24 1 67 1 0
#> 111.1 17.45 1 47 0 1
#> 78 23.88 1 43 0 0
#> 130 16.47 1 53 0 1
#> 32 20.90 1 37 1 0
#> 188 16.16 1 46 0 1
#> 155 13.08 1 26 0 0
#> 136 21.83 1 43 0 1
#> 60 13.15 1 38 1 0
#> 14 12.89 1 21 0 0
#> 61 10.12 1 36 0 1
#> 14.1 12.89 1 21 0 0
#> 128.1 20.35 1 35 0 1
#> 42 12.43 1 49 0 1
#> 55 19.34 1 69 0 1
#> 40 18.00 1 28 1 0
#> 129 23.41 1 53 1 0
#> 26.2 15.77 1 49 0 1
#> 164 23.60 1 76 0 1
#> 86 23.81 1 58 0 1
#> 61.1 10.12 1 36 0 1
#> 159 10.55 1 50 0 1
#> 175 21.91 1 43 0 0
#> 167 15.55 1 56 1 0
#> 140 12.68 1 59 1 0
#> 100 16.07 1 60 0 0
#> 52 10.42 1 52 0 1
#> 128.2 20.35 1 35 0 1
#> 60.1 13.15 1 38 1 0
#> 4 17.64 1 NA 0 1
#> 55.1 19.34 1 69 0 1
#> 96 14.54 1 33 0 1
#> 100.1 16.07 1 60 0 0
#> 40.1 18.00 1 28 1 0
#> 97.1 19.14 1 65 0 1
#> 10 10.53 1 34 0 0
#> 97.2 19.14 1 65 0 1
#> 157 15.10 1 47 0 0
#> 58 19.34 1 39 0 0
#> 26.3 15.77 1 49 0 1
#> 23 16.92 1 61 0 0
#> 113 22.86 1 34 0 0
#> 105 19.75 1 60 0 0
#> 57 14.46 1 45 0 1
#> 128.3 20.35 1 35 0 1
#> 36 21.19 1 48 0 1
#> 52.1 10.42 1 52 0 1
#> 117 17.46 1 26 0 1
#> 61.2 10.12 1 36 0 1
#> 99 21.19 1 38 0 1
#> 97.3 19.14 1 65 0 1
#> 199 19.81 1 NA 0 1
#> 92 22.92 1 47 0 1
#> 14.2 12.89 1 21 0 0
#> 129.1 23.41 1 53 1 0
#> 114.1 13.68 1 NA 0 0
#> 183.1 9.24 1 67 1 0
#> 192 16.44 1 31 1 0
#> 110 17.56 1 65 0 1
#> 197 21.60 1 69 1 0
#> 5.1 16.43 1 51 0 1
#> 108 18.29 1 39 0 1
#> 117.1 17.46 1 26 0 1
#> 92.1 22.92 1 47 0 1
#> 61.3 10.12 1 36 0 1
#> 170 19.54 1 43 0 1
#> 51 18.23 1 83 0 1
#> 56 12.21 1 60 0 0
#> 24 23.89 1 38 0 0
#> 49 12.19 1 48 1 0
#> 125 15.65 1 67 1 0
#> 101 9.97 1 10 0 1
#> 57.1 14.46 1 45 0 1
#> 91 5.33 1 61 0 1
#> 6 15.64 1 39 0 0
#> 167.1 15.55 1 56 1 0
#> 90 20.94 1 50 0 1
#> 192.1 16.44 1 31 1 0
#> 26.4 15.77 1 49 0 1
#> 181 16.46 1 45 0 1
#> 140.1 12.68 1 59 1 0
#> 78.1 23.88 1 43 0 0
#> 25.1 6.32 1 34 1 0
#> 88 18.37 1 47 0 0
#> 59 10.16 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 192.2 16.44 1 31 1 0
#> 129.2 23.41 1 53 1 0
#> 139 21.49 1 63 1 0
#> 79 16.23 1 54 1 0
#> 128.4 20.35 1 35 0 1
#> 124 9.73 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 41.1 18.02 1 40 1 0
#> 43 12.10 1 61 0 1
#> 14.3 12.89 1 21 0 0
#> 31 24.00 0 36 0 1
#> 142 24.00 0 53 0 0
#> 84 24.00 0 39 0 1
#> 71 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 165 24.00 0 47 0 0
#> 142.1 24.00 0 53 0 0
#> 126 24.00 0 48 0 0
#> 75 24.00 0 21 1 0
#> 82 24.00 0 34 0 0
#> 46 24.00 0 71 0 0
#> 165.1 24.00 0 47 0 0
#> 141 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 141.1 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 173 24.00 0 19 0 1
#> 178 24.00 0 52 1 0
#> 146 24.00 0 63 1 0
#> 46.1 24.00 0 71 0 0
#> 38 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 1 24.00 0 23 1 0
#> 28 24.00 0 67 1 0
#> 12 24.00 0 63 0 0
#> 162 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 87.1 24.00 0 27 0 0
#> 178.1 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 144 24.00 0 28 0 1
#> 109.1 24.00 0 48 0 0
#> 73 24.00 0 NA 0 1
#> 103 24.00 0 56 1 0
#> 132 24.00 0 55 0 0
#> 112 24.00 0 61 0 0
#> 11 24.00 0 42 0 1
#> 132.1 24.00 0 55 0 0
#> 11.1 24.00 0 42 0 1
#> 80 24.00 0 41 0 0
#> 44 24.00 0 56 0 0
#> 165.2 24.00 0 47 0 0
#> 31.1 24.00 0 36 0 1
#> 131 24.00 0 66 0 0
#> 84.1 24.00 0 39 0 1
#> 115 24.00 0 NA 1 0
#> 121 24.00 0 57 1 0
#> 200 24.00 0 64 0 0
#> 48 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 94 24.00 0 51 0 1
#> 182 24.00 0 35 0 0
#> 21 24.00 0 47 0 0
#> 103.1 24.00 0 56 1 0
#> 116 24.00 0 58 0 1
#> 47 24.00 0 38 0 1
#> 21.1 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 17 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 186 24.00 0 45 1 0
#> 46.2 24.00 0 71 0 0
#> 82.1 24.00 0 34 0 0
#> 141.2 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 84.2 24.00 0 39 0 1
#> 121.1 24.00 0 57 1 0
#> 102 24.00 0 49 0 0
#> 11.2 24.00 0 42 0 1
#> 67 24.00 0 25 0 0
#> 84.3 24.00 0 39 0 1
#> 142.2 24.00 0 53 0 0
#> 31.2 24.00 0 36 0 1
#> 19 24.00 0 57 0 1
#> 38.1 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 17.1 24.00 0 38 0 1
#> 132.2 24.00 0 55 0 0
#> 132.3 24.00 0 55 0 0
#> 135 24.00 0 58 1 0
#> 174 24.00 0 49 1 0
#> 53 24.00 0 32 0 1
#> 132.4 24.00 0 55 0 0
#> 67.1 24.00 0 25 0 0
#> 19.1 24.00 0 57 0 1
#> 82.2 24.00 0 34 0 0
#> 33 24.00 0 53 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.948 NA NA NA
#> 2 age, Cure model 0.00505 NA NA NA
#> 3 grade_ii, Cure model 1.01 NA NA NA
#> 4 grade_iii, Cure model 1.61 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00740 NA NA NA
#> 2 grade_ii, Survival model 0.461 NA NA NA
#> 3 grade_iii, Survival model 0.381 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.947776 0.005048 1.007632 1.613860
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 242.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.947775743 0.005047866 1.007632405 1.613859904
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007398286 0.461248359 0.381295921
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.800820551 0.518724917 0.218238897 0.962203011 0.208357963 0.575176372
#> [7] 0.575176372 0.309516210 0.659138198 0.971706352 0.158562092 0.443256722
#> [13] 0.848566876 0.706597766 0.943310261 0.443256722 0.011981091 0.471720667
#> [19] 0.198400428 0.546854479 0.734906631 0.127957424 0.716108780 0.744387798
#> [25] 0.896311301 0.744387798 0.218238897 0.810351061 0.281353930 0.395704618
#> [31] 0.052174776 0.575176372 0.040627977 0.029616397 0.896311301 0.858123291
#> [37] 0.117728822 0.640240392 0.781863911 0.556272409 0.877257147 0.218238897
#> [43] 0.716108780 0.281353930 0.678184799 0.556272409 0.395704618 0.309516210
#> [49] 0.867678489 0.309516210 0.668641579 0.281353930 0.575176372 0.462119238
#> [55] 0.107737159 0.262220505 0.687708321 0.218238897 0.168741865 0.877257147
#> [61] 0.424366884 0.896311301 0.168741865 0.309516210 0.089048118 0.744387798
#> [67] 0.052174776 0.943310261 0.490918262 0.414724248 0.138133442 0.518724917
#> [73] 0.356746784 0.424366884 0.089048118 0.896311301 0.271798177 0.366554499
#> [79] 0.819879448 0.003185781 0.829447696 0.621209809 0.933822580 0.687708321
#> [85] 0.990534599 0.630707109 0.640240392 0.188338872 0.490918262 0.575176372
#> [91] 0.481324205 0.781863911 0.011981091 0.971706352 0.346912808 0.376417026
#> [97] 0.490918262 0.052174776 0.148345929 0.537429765 0.218238897 0.079086703
#> [103] 0.376417026 0.839003604 0.744387798 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 37 5 128 77 190 26 26.1 97 18 25 153 111 107
#> 12.52 16.43 20.35 7.27 20.81 15.77 15.77 19.14 15.21 6.32 21.33 17.45 11.18
#> 13 183 111.1 78 130 32 188 155 136 60 14 61 14.1
#> 14.34 9.24 17.45 23.88 16.47 20.90 16.16 13.08 21.83 13.15 12.89 10.12 12.89
#> 128.1 42 55 40 129 26.2 164 86 61.1 159 175 167 140
#> 20.35 12.43 19.34 18.00 23.41 15.77 23.60 23.81 10.12 10.55 21.91 15.55 12.68
#> 100 52 128.2 60.1 55.1 96 100.1 40.1 97.1 10 97.2 157 58
#> 16.07 10.42 20.35 13.15 19.34 14.54 16.07 18.00 19.14 10.53 19.14 15.10 19.34
#> 26.3 23 113 105 57 128.3 36 52.1 117 61.2 99 97.3 92
#> 15.77 16.92 22.86 19.75 14.46 20.35 21.19 10.42 17.46 10.12 21.19 19.14 22.92
#> 14.2 129.1 183.1 192 110 197 5.1 108 117.1 92.1 61.3 170 51
#> 12.89 23.41 9.24 16.44 17.56 21.60 16.43 18.29 17.46 22.92 10.12 19.54 18.23
#> 56 24 49 125 101 57.1 91 6 167.1 90 192.1 26.4 181
#> 12.21 23.89 12.19 15.65 9.97 14.46 5.33 15.64 15.55 20.94 16.44 15.77 16.46
#> 140.1 78.1 25.1 88 41 192.2 129.2 139 79 128.4 69 41.1 43
#> 12.68 23.88 6.32 18.37 18.02 16.44 23.41 21.49 16.23 20.35 23.23 18.02 12.10
#> 14.3 31 142 84 71 22 165 142.1 126 75 82 46 165.1
#> 12.89 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 185 141.1 120 173 178 146 46.1 38 87 1 28 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 152 3 87.1 178.1 109 144 109.1 103 132 112 11 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 80 44 165.2 31.1 131 84.1 121 200 48 34 94 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 103.1 116 47 21.1 122 17 83 186 46.2 82.1 141.2 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84.2 121.1 102 11.2 67 84.3 142.2 31.2 19 38.1 65 17.1 132.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.3 135 174 53 132.4 67.1 19.1 82.2 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[4]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003521632 0.865971941 0.333507394
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.601379339 0.009642563 0.073918180
#> grade_iii, Cure model
#> 0.899483905
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 125 15.65 1 67 1 0
#> 16 8.71 1 71 0 1
#> 169 22.41 1 46 0 0
#> 18 15.21 1 49 1 0
#> 145 10.07 1 65 1 0
#> 184 17.77 1 38 0 0
#> 26 15.77 1 49 0 1
#> 55 19.34 1 69 0 1
#> 6 15.64 1 39 0 0
#> 40 18.00 1 28 1 0
#> 153 21.33 1 55 1 0
#> 91 5.33 1 61 0 1
#> 78 23.88 1 43 0 0
#> 195 11.76 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 86 23.81 1 58 0 1
#> 197 21.60 1 69 1 0
#> 29 15.45 1 68 1 0
#> 168 23.72 1 70 0 0
#> 110 17.56 1 65 0 1
#> 117 17.46 1 26 0 1
#> 188 16.16 1 46 0 1
#> 125.1 15.65 1 67 1 0
#> 171 16.57 1 41 0 1
#> 93 10.33 1 52 0 1
#> 180 14.82 1 37 0 0
#> 88 18.37 1 47 0 0
#> 106 16.67 1 49 1 0
#> 57 14.46 1 45 0 1
#> 171.1 16.57 1 41 0 1
#> 177 12.53 1 75 0 0
#> 111 17.45 1 47 0 1
#> 199 19.81 1 NA 0 1
#> 26.1 15.77 1 49 0 1
#> 113 22.86 1 34 0 0
#> 149 8.37 1 33 1 0
#> 175 21.91 1 43 0 0
#> 149.1 8.37 1 33 1 0
#> 179 18.63 1 42 0 0
#> 70 7.38 1 30 1 0
#> 188.1 16.16 1 46 0 1
#> 59 10.16 1 NA 1 0
#> 113.1 22.86 1 34 0 0
#> 154 12.63 1 20 1 0
#> 100 16.07 1 60 0 0
#> 50 10.02 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 15 22.68 1 48 0 0
#> 194 22.40 1 38 0 1
#> 164 23.60 1 76 0 1
#> 92 22.92 1 47 0 1
#> 145.1 10.07 1 65 1 0
#> 195.1 11.76 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 125.2 15.65 1 67 1 0
#> 23 16.92 1 61 0 0
#> 59.1 10.16 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 58 19.34 1 39 0 0
#> 181 16.46 1 45 0 1
#> 113.2 22.86 1 34 0 0
#> 128 20.35 1 35 0 1
#> 164.1 23.60 1 76 0 1
#> 166 19.98 1 48 0 0
#> 106.1 16.67 1 49 1 0
#> 110.1 17.56 1 65 0 1
#> 16.1 8.71 1 71 0 1
#> 170 19.54 1 43 0 1
#> 175.1 21.91 1 43 0 0
#> 117.1 17.46 1 26 0 1
#> 134 17.81 1 47 1 0
#> 50.1 10.02 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 110.2 17.56 1 65 0 1
#> 100.1 16.07 1 60 0 0
#> 183 9.24 1 67 1 0
#> 70.1 7.38 1 30 1 0
#> 92.1 22.92 1 47 0 1
#> 134.1 17.81 1 47 1 0
#> 79 16.23 1 54 1 0
#> 58.1 19.34 1 39 0 0
#> 139 21.49 1 63 1 0
#> 57.1 14.46 1 45 0 1
#> 136 21.83 1 43 0 1
#> 117.2 17.46 1 26 0 1
#> 32 20.90 1 37 1 0
#> 175.2 21.91 1 43 0 0
#> 29.1 15.45 1 68 1 0
#> 43 12.10 1 61 0 1
#> 55.1 19.34 1 69 0 1
#> 127 3.53 1 62 0 1
#> 68 20.62 1 44 0 0
#> 50.2 10.02 1 NA 1 0
#> 93.1 10.33 1 52 0 1
#> 158 20.14 1 74 1 0
#> 194.1 22.40 1 38 0 1
#> 93.2 10.33 1 52 0 1
#> 16.2 8.71 1 71 0 1
#> 13 14.34 1 54 0 1
#> 154.1 12.63 1 20 1 0
#> 93.3 10.33 1 52 0 1
#> 15.1 22.68 1 48 0 0
#> 36 21.19 1 48 0 1
#> 32.1 20.90 1 37 1 0
#> 154.2 12.63 1 20 1 0
#> 23.1 16.92 1 61 0 0
#> 113.3 22.86 1 34 0 0
#> 56 12.21 1 60 0 0
#> 97 19.14 1 65 0 1
#> 26.2 15.77 1 49 0 1
#> 86.1 23.81 1 58 0 1
#> 86.2 23.81 1 58 0 1
#> 1 24.00 0 23 1 0
#> 118 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 35 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 82 24.00 0 34 0 0
#> 7 24.00 0 37 1 0
#> 17 24.00 0 38 0 1
#> 115 24.00 0 NA 1 0
#> 193 24.00 0 45 0 1
#> 176 24.00 0 43 0 1
#> 7.1 24.00 0 37 1 0
#> 144 24.00 0 28 0 1
#> 102 24.00 0 49 0 0
#> 71 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 62 24.00 0 71 0 0
#> 186 24.00 0 45 1 0
#> 33 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 142 24.00 0 53 0 0
#> 176.1 24.00 0 43 0 1
#> 182 24.00 0 35 0 0
#> 47 24.00 0 38 0 1
#> 20 24.00 0 46 1 0
#> 161 24.00 0 45 0 0
#> 27 24.00 0 63 1 0
#> 62.1 24.00 0 71 0 0
#> 98 24.00 0 34 1 0
#> 102.1 24.00 0 49 0 0
#> 48 24.00 0 31 1 0
#> 7.2 24.00 0 37 1 0
#> 2 24.00 0 9 0 0
#> 156 24.00 0 50 1 0
#> 120 24.00 0 68 0 1
#> 27.1 24.00 0 63 1 0
#> 19 24.00 0 57 0 1
#> 103 24.00 0 56 1 0
#> 193.1 24.00 0 45 0 1
#> 82.1 24.00 0 34 0 0
#> 176.2 24.00 0 43 0 1
#> 137 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 98.1 24.00 0 34 1 0
#> 151 24.00 0 42 0 0
#> 182.1 24.00 0 35 0 0
#> 131 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 82.2 24.00 0 34 0 0
#> 118.1 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 35.1 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 20.1 24.00 0 46 1 0
#> 112 24.00 0 61 0 0
#> 82.3 24.00 0 34 0 0
#> 12.1 24.00 0 63 0 0
#> 82.4 24.00 0 34 0 0
#> 104.1 24.00 0 50 1 0
#> 67 24.00 0 25 0 0
#> 98.2 24.00 0 34 1 0
#> 151.1 24.00 0 42 0 0
#> 156.1 24.00 0 50 1 0
#> 64 24.00 0 43 0 0
#> 120.1 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 200 24.00 0 64 0 0
#> 198.1 24.00 0 66 0 1
#> 84 24.00 0 39 0 1
#> 146 24.00 0 63 1 0
#> 53 24.00 0 32 0 1
#> 38 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 193.2 24.00 0 45 0 1
#> 12.2 24.00 0 63 0 0
#> 31 24.00 0 36 0 1
#> 116 24.00 0 58 0 1
#> 147 24.00 0 76 1 0
#> 156.2 24.00 0 50 1 0
#> 47.1 24.00 0 38 0 1
#> 20.2 24.00 0 46 1 0
#> 83 24.00 0 6 0 0
#> 176.3 24.00 0 43 0 1
#> 103.1 24.00 0 56 1 0
#> 33.1 24.00 0 53 0 0
#> 87 24.00 0 27 0 0
#> 103.2 24.00 0 56 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.601 NA NA NA
#> 2 age, Cure model 0.00964 NA NA NA
#> 3 grade_ii, Cure model 0.0739 NA NA NA
#> 4 grade_iii, Cure model 0.899 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00352 NA NA NA
#> 2 grade_ii, Survival model 0.866 NA NA NA
#> 3 grade_iii, Survival model 0.334 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.601379 0.009643 0.073918 0.899484
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 252.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.601379339 0.009642563 0.073918180 0.899483905
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003521632 0.865971941 0.333507394
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.72752774 0.93342952 0.21245736 0.77695766 0.91060066 0.52451529
#> [7] 0.70200567 0.41935238 0.75228765 0.49651481 0.31794201 0.98538820
#> [13] 0.01016554 0.81737711 0.03254099 0.29506178 0.76064510 0.06566170
#> [19] 0.53380363 0.56103293 0.66762887 0.72752774 0.63268244 0.87993253
#> [25] 0.78507153 0.48666574 0.61508908 0.79319566 0.63268244 0.84866418
#> [31] 0.58790555 0.70200567 0.13028653 0.95597911 0.24812067 0.95597911
#> [37] 0.46704972 0.97081048 0.66762887 0.13028653 0.82546325 0.68477618
#> [43] 0.85648608 0.18877950 0.22475157 0.08002526 0.10568513 0.91060066
#> [49] 0.32882043 0.72752774 0.59697746 0.17678777 0.41935238 0.65017458
#> [55] 0.13028653 0.37985358 0.08002526 0.39969386 0.61508908 0.53380363
#> [61] 0.93342952 0.40954667 0.24812067 0.56103293 0.50614348 0.47684698
#> [67] 0.53380363 0.68477618 0.92583554 0.97081048 0.10568513 0.50614348
#> [73] 0.65895753 0.41935238 0.30669474 0.79319566 0.28301847 0.56103293
#> [79] 0.34994320 0.24812067 0.76064510 0.87211845 0.41935238 0.99269738
#> [85] 0.36976620 0.87993253 0.38987869 0.22475157 0.87993253 0.93342952
#> [91] 0.80929796 0.82546325 0.87993253 0.18877950 0.32882043 0.34994320
#> [97] 0.82546325 0.59697746 0.13028653 0.86429554 0.45728065 0.70200567
#> [103] 0.03254099 0.03254099 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 125 16 169 18 145 184 26 55 6 40 153 91 78
#> 15.65 8.71 22.41 15.21 10.07 17.77 15.77 19.34 15.64 18.00 21.33 5.33 23.88
#> 155 86 197 29 168 110 117 188 125.1 171 93 180 88
#> 13.08 23.81 21.60 15.45 23.72 17.56 17.46 16.16 15.65 16.57 10.33 14.82 18.37
#> 106 57 171.1 177 111 26.1 113 149 175 149.1 179 70 188.1
#> 16.67 14.46 16.57 12.53 17.45 15.77 22.86 8.37 21.91 8.37 18.63 7.38 16.16
#> 113.1 154 100 42 15 194 164 92 145.1 99 125.2 23 63
#> 22.86 12.63 16.07 12.43 22.68 22.40 23.60 22.92 10.07 21.19 15.65 16.92 22.77
#> 58 181 113.2 128 164.1 166 106.1 110.1 16.1 170 175.1 117.1 134
#> 19.34 16.46 22.86 20.35 23.60 19.98 16.67 17.56 8.71 19.54 21.91 17.46 17.81
#> 8 110.2 100.1 183 70.1 92.1 134.1 79 58.1 139 57.1 136 117.2
#> 18.43 17.56 16.07 9.24 7.38 22.92 17.81 16.23 19.34 21.49 14.46 21.83 17.46
#> 32 175.2 29.1 43 55.1 127 68 93.1 158 194.1 93.2 16.2 13
#> 20.90 21.91 15.45 12.10 19.34 3.53 20.62 10.33 20.14 22.40 10.33 8.71 14.34
#> 154.1 93.3 15.1 36 32.1 154.2 23.1 113.3 56 97 26.2 86.1 86.2
#> 12.63 10.33 22.68 21.19 20.90 12.63 16.92 22.86 12.21 19.14 15.77 23.81 23.81
#> 1 118 12 35 95 82 7 17 193 176 7.1 144 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 165 62 186 33 198 142 176.1 182 47 20 161 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.1 98 102.1 48 7.2 2 156 120 27.1 19 103 193.1 82.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.2 137 65 98.1 151 182.1 131 174 82.2 118.1 104 35.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 112 82.3 12.1 82.4 104.1 67 98.2 151.1 156.1 64 120.1 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 200 198.1 84 146 53 38 193.2 12.2 31 116 147 156.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 20.2 83 176.3 103.1 33.1 87 103.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[5]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.000104876 1.024979338 0.603690602
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.292568756 0.003996585 -0.066227377
#> grade_iii, Cure model
#> 1.201760600
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 8 18.43 1 32 0 0
#> 29 15.45 1 68 1 0
#> 105 19.75 1 60 0 0
#> 78 23.88 1 43 0 0
#> 108 18.29 1 39 0 1
#> 96 14.54 1 33 0 1
#> 18 15.21 1 49 1 0
#> 37 12.52 1 57 1 0
#> 194 22.40 1 38 0 1
#> 125 15.65 1 67 1 0
#> 168 23.72 1 70 0 0
#> 57 14.46 1 45 0 1
#> 101 9.97 1 10 0 1
#> 79 16.23 1 54 1 0
#> 175 21.91 1 43 0 0
#> 8.1 18.43 1 32 0 0
#> 51 18.23 1 83 0 1
#> 107 11.18 1 54 1 0
#> 130 16.47 1 53 0 1
#> 77 7.27 1 67 0 1
#> 157 15.10 1 47 0 0
#> 123 13.00 1 44 1 0
#> 40 18.00 1 28 1 0
#> 90 20.94 1 50 0 1
#> 96.1 14.54 1 33 0 1
#> 61 10.12 1 36 0 1
#> 100 16.07 1 60 0 0
#> 181 16.46 1 45 0 1
#> 88 18.37 1 47 0 0
#> 194.1 22.40 1 38 0 1
#> 166 19.98 1 48 0 0
#> 167 15.55 1 56 1 0
#> 26 15.77 1 49 0 1
#> 130.1 16.47 1 53 0 1
#> 24 23.89 1 38 0 0
#> 184 17.77 1 38 0 0
#> 25 6.32 1 34 1 0
#> 89 11.44 1 NA 0 0
#> 56 12.21 1 60 0 0
#> 25.1 6.32 1 34 1 0
#> 13 14.34 1 54 0 1
#> 136 21.83 1 43 0 1
#> 66 22.13 1 53 0 0
#> 164 23.60 1 76 0 1
#> 187 9.92 1 39 1 0
#> 110 17.56 1 65 0 1
#> 175.1 21.91 1 43 0 0
#> 136.1 21.83 1 43 0 1
#> 51.1 18.23 1 83 0 1
#> 129 23.41 1 53 1 0
#> 181.1 16.46 1 45 0 1
#> 69 23.23 1 25 0 1
#> 150 20.33 1 48 0 0
#> 154 12.63 1 20 1 0
#> 61.1 10.12 1 36 0 1
#> 179 18.63 1 42 0 0
#> 51.2 18.23 1 83 0 1
#> 114 13.68 1 NA 0 0
#> 183 9.24 1 67 1 0
#> 79.1 16.23 1 54 1 0
#> 39 15.59 1 37 0 1
#> 5 16.43 1 51 0 1
#> 50 10.02 1 NA 1 0
#> 57.1 14.46 1 45 0 1
#> 184.1 17.77 1 38 0 0
#> 175.2 21.91 1 43 0 0
#> 127 3.53 1 62 0 1
#> 60 13.15 1 38 1 0
#> 169 22.41 1 46 0 0
#> 86 23.81 1 58 0 1
#> 78.1 23.88 1 43 0 0
#> 107.1 11.18 1 54 1 0
#> 106 16.67 1 49 1 0
#> 43 12.10 1 61 0 1
#> 101.1 9.97 1 10 0 1
#> 129.1 23.41 1 53 1 0
#> 125.1 15.65 1 67 1 0
#> 100.1 16.07 1 60 0 0
#> 153 21.33 1 55 1 0
#> 91 5.33 1 61 0 1
#> 168.1 23.72 1 70 0 0
#> 145 10.07 1 65 1 0
#> 40.1 18.00 1 28 1 0
#> 113 22.86 1 34 0 0
#> 157.1 15.10 1 47 0 0
#> 85 16.44 1 36 0 0
#> 124 9.73 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 76 19.22 1 54 0 1
#> 14 12.89 1 21 0 0
#> 169.1 22.41 1 46 0 0
#> 69.1 23.23 1 25 0 1
#> 14.1 12.89 1 21 0 0
#> 99 21.19 1 38 0 1
#> 78.2 23.88 1 43 0 0
#> 145.1 10.07 1 65 1 0
#> 105.1 19.75 1 60 0 0
#> 107.2 11.18 1 54 1 0
#> 50.1 10.02 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 58 19.34 1 39 0 0
#> 99.1 21.19 1 38 0 1
#> 157.2 15.10 1 47 0 0
#> 177.1 12.53 1 75 0 0
#> 190 20.81 1 42 1 0
#> 192 16.44 1 31 1 0
#> 43.1 12.10 1 61 0 1
#> 130.2 16.47 1 53 0 1
#> 181.2 16.46 1 45 0 1
#> 61.2 10.12 1 36 0 1
#> 59 10.16 1 NA 1 0
#> 175.3 21.91 1 43 0 0
#> 103 24.00 0 56 1 0
#> 186 24.00 0 45 1 0
#> 74 24.00 0 43 0 1
#> 176 24.00 0 43 0 1
#> 156 24.00 0 50 1 0
#> 118 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 48 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 82 24.00 0 34 0 0
#> 46 24.00 0 71 0 0
#> 178 24.00 0 52 1 0
#> 162 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 119 24.00 0 17 0 0
#> 151 24.00 0 42 0 0
#> 31 24.00 0 36 0 1
#> 152 24.00 0 36 0 1
#> 65.1 24.00 0 57 1 0
#> 112 24.00 0 61 0 0
#> 7 24.00 0 37 1 0
#> 74.1 24.00 0 43 0 1
#> 3 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 27 24.00 0 63 1 0
#> 2.1 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 34 24.00 0 36 0 0
#> 176.1 24.00 0 43 0 1
#> 138 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 48.1 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 82.1 24.00 0 34 0 0
#> 7.1 24.00 0 37 1 0
#> 1 24.00 0 23 1 0
#> 71 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 165 24.00 0 47 0 0
#> 72.1 24.00 0 40 0 1
#> 33 24.00 0 53 0 0
#> 135 24.00 0 58 1 0
#> 138.1 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 162.1 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 2.2 24.00 0 9 0 0
#> 112.2 24.00 0 61 0 0
#> 147 24.00 0 76 1 0
#> 21.1 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 178.1 24.00 0 52 1 0
#> 126.1 24.00 0 48 0 0
#> 135.1 24.00 0 58 1 0
#> 71.1 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 73 24.00 0 NA 0 1
#> 33.1 24.00 0 53 0 0
#> 102 24.00 0 49 0 0
#> 137 24.00 0 45 1 0
#> 54 24.00 0 53 1 0
#> 156.1 24.00 0 50 1 0
#> 62.1 24.00 0 71 0 0
#> 162.2 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 12 24.00 0 63 0 0
#> 176.2 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 87 24.00 0 27 0 0
#> 121 24.00 0 57 1 0
#> 178.2 24.00 0 52 1 0
#> 67.1 24.00 0 25 0 0
#> 28 24.00 0 67 1 0
#> 142 24.00 0 53 0 0
#> 7.2 24.00 0 37 1 0
#> 62.2 24.00 0 71 0 0
#> 161 24.00 0 45 0 0
#> 71.2 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 120 24.00 0 68 0 1
#> 116.1 24.00 0 58 0 1
#> 163.1 24.00 0 66 0 0
#> 193 24.00 0 45 0 1
#> 98 24.00 0 34 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.293 NA NA NA
#> 2 age, Cure model 0.00400 NA NA NA
#> 3 grade_ii, Cure model -0.0662 NA NA NA
#> 4 grade_iii, Cure model 1.20 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000105 NA NA NA
#> 2 grade_ii, Survival model 1.02 NA NA NA
#> 3 grade_iii, Survival model 0.604 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.292569 0.003997 -0.066227 1.201761
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 252.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.292568756 0.003996585 -0.066227377 1.201760600
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.000104876 1.024979338 0.603690602
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.51535087 0.77344544 0.46677297 0.05492153 0.54415787 0.80642064
#> [7] 0.78015377 0.88195982 0.29105941 0.74582726 0.13860134 0.81940635
#> [13] 0.95155041 0.70967488 0.32703194 0.51535087 0.55368011 0.90607666
#> [19] 0.64023985 0.97350149 0.78676138 0.84492791 0.58064707 0.42709611
#> [25] 0.80642064 0.92336973 0.72414370 0.66395061 0.53449676 0.29105941
#> [31] 0.45695423 0.76663268 0.73861434 0.64023985 0.02012398 0.59781427
#> [37] 0.97890392 0.88803225 0.97890392 0.83222543 0.37302541 0.31488316
#> [43] 0.17919673 0.96259317 0.61498347 0.32703194 0.37302541 0.55368011
#> [49] 0.19886992 0.66395061 0.22694862 0.44713656 0.86356094 0.92336973
#> [55] 0.50568857 0.55368011 0.96807448 0.70967488 0.75971101 0.70212933
#> [61] 0.81940635 0.59781427 0.32703194 0.99474750 0.83861938 0.26552053
#> [67] 0.11665217 0.05492153 0.90607666 0.63198318 0.89410495 0.95155041
#> [73] 0.19886992 0.74582726 0.72414370 0.39559963 0.98947224 0.13860134
#> [79] 0.94040065 0.58064707 0.25243552 0.78676138 0.68698675 0.62353074
#> [85] 0.49602710 0.85115397 0.26552053 0.22694862 0.85115397 0.40649401
#> [91] 0.05492153 0.94040065 0.46677297 0.90607666 0.86970793 0.48620911
#> [97] 0.40649401 0.78676138 0.86970793 0.43731997 0.68698675 0.89410495
#> [103] 0.64023985 0.66395061 0.92336973 0.32703194 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 8 29 105 78 108 96 18 37 194 125 168 57 101
#> 18.43 15.45 19.75 23.88 18.29 14.54 15.21 12.52 22.40 15.65 23.72 14.46 9.97
#> 79 175 8.1 51 107 130 77 157 123 40 90 96.1 61
#> 16.23 21.91 18.43 18.23 11.18 16.47 7.27 15.10 13.00 18.00 20.94 14.54 10.12
#> 100 181 88 194.1 166 167 26 130.1 24 184 25 56 25.1
#> 16.07 16.46 18.37 22.40 19.98 15.55 15.77 16.47 23.89 17.77 6.32 12.21 6.32
#> 13 136 66 164 187 110 175.1 136.1 51.1 129 181.1 69 150
#> 14.34 21.83 22.13 23.60 9.92 17.56 21.91 21.83 18.23 23.41 16.46 23.23 20.33
#> 154 61.1 179 51.2 183 79.1 39 5 57.1 184.1 175.2 127 60
#> 12.63 10.12 18.63 18.23 9.24 16.23 15.59 16.43 14.46 17.77 21.91 3.53 13.15
#> 169 86 78.1 107.1 106 43 101.1 129.1 125.1 100.1 153 91 168.1
#> 22.41 23.81 23.88 11.18 16.67 12.10 9.97 23.41 15.65 16.07 21.33 5.33 23.72
#> 145 40.1 113 157.1 85 45 76 14 169.1 69.1 14.1 99 78.2
#> 10.07 18.00 22.86 15.10 16.44 17.42 19.22 12.89 22.41 23.23 12.89 21.19 23.88
#> 145.1 105.1 107.2 177 58 99.1 157.2 177.1 190 192 43.1 130.2 181.2
#> 10.07 19.75 11.18 12.53 19.34 21.19 15.10 12.53 20.81 16.44 12.10 16.47 16.46
#> 61.2 175.3 103 186 74 176 156 118 182 48 65 82 46
#> 10.12 21.91 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 162 2 119 151 31 152 65.1 112 7 74.1 3 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 2.1 172 72 34 176.1 138 19 48.1 185 163 141 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 7.1 1 71 21 165 72.1 33 135 138.1 126 162.1 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.2 112.2 147 21.1 131 178.1 126.1 135.1 71.1 67 33.1 102 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 156.1 62.1 162.2 20 12 176.2 146 87 121 178.2 67.1 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 7.2 62.2 161 71.2 116 120 116.1 163.1 193 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[6]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006060728 0.200420224 -0.563627474
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.359479830 0.009960809 0.011246246
#> grade_iii, Cure model
#> 0.206756546
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 69 23.23 1 25 0 1
#> 166 19.98 1 48 0 0
#> 4 17.64 1 NA 0 1
#> 177 12.53 1 75 0 0
#> 128 20.35 1 35 0 1
#> 100 16.07 1 60 0 0
#> 175 21.91 1 43 0 0
#> 170 19.54 1 43 0 1
#> 39 15.59 1 37 0 1
#> 40 18.00 1 28 1 0
#> 159 10.55 1 50 0 1
#> 149 8.37 1 33 1 0
#> 124 9.73 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 169 22.41 1 46 0 0
#> 92 22.92 1 47 0 1
#> 164.1 23.60 1 76 0 1
#> 55 19.34 1 69 0 1
#> 125 15.65 1 67 1 0
#> 133 14.65 1 57 0 0
#> 32 20.90 1 37 1 0
#> 18 15.21 1 49 1 0
#> 107 11.18 1 54 1 0
#> 111 17.45 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 30 17.43 1 78 0 0
#> 32.1 20.90 1 37 1 0
#> 4.1 17.64 1 NA 0 1
#> 192 16.44 1 31 1 0
#> 145 10.07 1 65 1 0
#> 43 12.10 1 61 0 1
#> 50 10.02 1 NA 1 0
#> 197 21.60 1 69 1 0
#> 136 21.83 1 43 0 1
#> 179 18.63 1 42 0 0
#> 139 21.49 1 63 1 0
#> 56 12.21 1 60 0 0
#> 159.1 10.55 1 50 0 1
#> 97 19.14 1 65 0 1
#> 30.1 17.43 1 78 0 0
#> 127 3.53 1 62 0 1
#> 195 11.76 1 NA 1 0
#> 136.1 21.83 1 43 0 1
#> 70 7.38 1 30 1 0
#> 133.1 14.65 1 57 0 0
#> 190 20.81 1 42 1 0
#> 25 6.32 1 34 1 0
#> 184 17.77 1 38 0 0
#> 167 15.55 1 56 1 0
#> 195.1 11.76 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 117 17.46 1 26 0 1
#> 150 20.33 1 48 0 0
#> 187 9.92 1 39 1 0
#> 14 12.89 1 21 0 0
#> 158 20.14 1 74 1 0
#> 134 17.81 1 47 1 0
#> 18.1 15.21 1 49 1 0
#> 58 19.34 1 39 0 0
#> 81 14.06 1 34 0 0
#> 159.2 10.55 1 50 0 1
#> 183 9.24 1 67 1 0
#> 158.1 20.14 1 74 1 0
#> 127.1 3.53 1 62 0 1
#> 123 13.00 1 44 1 0
#> 88 18.37 1 47 0 0
#> 8 18.43 1 32 0 0
#> 125.1 15.65 1 67 1 0
#> 100.1 16.07 1 60 0 0
#> 175.1 21.91 1 43 0 0
#> 134.1 17.81 1 47 1 0
#> 154 12.63 1 20 1 0
#> 125.2 15.65 1 67 1 0
#> 86 23.81 1 58 0 1
#> 177.1 12.53 1 75 0 0
#> 111.1 17.45 1 47 0 1
#> 77 7.27 1 67 0 1
#> 133.2 14.65 1 57 0 0
#> 57 14.46 1 45 0 1
#> 10 10.53 1 34 0 0
#> 10.1 10.53 1 34 0 0
#> 166.1 19.98 1 48 0 0
#> 157 15.10 1 47 0 0
#> 114.1 13.68 1 NA 0 0
#> 85 16.44 1 36 0 0
#> 167.1 15.55 1 56 1 0
#> 55.1 19.34 1 69 0 1
#> 195.2 11.76 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 10.2 10.53 1 34 0 0
#> 100.2 16.07 1 60 0 0
#> 107.1 11.18 1 54 1 0
#> 187.1 9.92 1 39 1 0
#> 117.1 17.46 1 26 0 1
#> 184.1 17.77 1 38 0 0
#> 125.3 15.65 1 67 1 0
#> 60 13.15 1 38 1 0
#> 70.1 7.38 1 30 1 0
#> 88.1 18.37 1 47 0 0
#> 45 17.42 1 54 0 1
#> 91 5.33 1 61 0 1
#> 29 15.45 1 68 1 0
#> 197.1 21.60 1 69 1 0
#> 134.2 17.81 1 47 1 0
#> 167.2 15.55 1 56 1 0
#> 77.1 7.27 1 67 0 1
#> 41 18.02 1 40 1 0
#> 81.1 14.06 1 34 0 0
#> 56.1 12.21 1 60 0 0
#> 123.1 13.00 1 44 1 0
#> 92.1 22.92 1 47 0 1
#> 73 24.00 0 NA 0 1
#> 28 24.00 0 67 1 0
#> 138 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 198 24.00 0 66 0 1
#> 75 24.00 0 21 1 0
#> 73.1 24.00 0 NA 0 1
#> 193 24.00 0 45 0 1
#> 112 24.00 0 61 0 0
#> 31 24.00 0 36 0 1
#> 19 24.00 0 57 0 1
#> 11 24.00 0 42 0 1
#> 27 24.00 0 63 1 0
#> 120 24.00 0 68 0 1
#> 7 24.00 0 37 1 0
#> 137 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 141 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 7.1 24.00 0 37 1 0
#> 62 24.00 0 71 0 0
#> 198.1 24.00 0 66 0 1
#> 7.2 24.00 0 37 1 0
#> 137.1 24.00 0 45 1 0
#> 147 24.00 0 76 1 0
#> 147.1 24.00 0 76 1 0
#> 44 24.00 0 56 0 0
#> 176 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 3 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 38 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 27.1 24.00 0 63 1 0
#> 138.1 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 120.1 24.00 0 68 0 1
#> 178 24.00 0 52 1 0
#> 144 24.00 0 28 0 1
#> 74 24.00 0 43 0 1
#> 156 24.00 0 50 1 0
#> 162 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 2 24.00 0 9 0 0
#> 141.1 24.00 0 44 1 0
#> 28.1 24.00 0 67 1 0
#> 163 24.00 0 66 0 0
#> 162.1 24.00 0 51 0 0
#> 173.1 24.00 0 19 0 1
#> 135.1 24.00 0 58 1 0
#> 74.1 24.00 0 43 0 1
#> 71 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 44.1 24.00 0 56 0 0
#> 35 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 3.1 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 173.2 24.00 0 19 0 1
#> 94 24.00 0 51 0 1
#> 74.2 24.00 0 43 0 1
#> 118 24.00 0 44 1 0
#> 62.1 24.00 0 71 0 0
#> 27.2 24.00 0 63 1 0
#> 73.2 24.00 0 NA 0 1
#> 119 24.00 0 17 0 0
#> 182 24.00 0 35 0 0
#> 191 24.00 0 60 0 1
#> 135.2 24.00 0 58 1 0
#> 20 24.00 0 46 1 0
#> 46 24.00 0 71 0 0
#> 119.1 24.00 0 17 0 0
#> 138.2 24.00 0 44 1 0
#> 165.1 24.00 0 47 0 0
#> 143.1 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 138.3 24.00 0 44 1 0
#> 163.1 24.00 0 66 0 0
#> 62.2 24.00 0 71 0 0
#> 141.2 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 122 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 74.3 24.00 0 43 0 1
#> 87 24.00 0 27 0 0
#> 17 24.00 0 38 0 1
#> 44.2 24.00 0 56 0 0
#> 74.4 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.359 NA NA NA
#> 2 age, Cure model 0.00996 NA NA NA
#> 3 grade_ii, Cure model 0.0112 NA NA NA
#> 4 grade_iii, Cure model 0.207 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00606 NA NA NA
#> 2 grade_ii, Survival model 0.200 NA NA NA
#> 3 grade_iii, Survival model -0.564 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.359480 0.009961 0.011246 0.206757
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.9
#> Residual Deviance: 257.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.359479830 0.009960809 0.011246246 0.206756546
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006060728 0.200420224 -0.563627474
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 1.486171e-02 2.597476e-03 1.037676e-01 6.649487e-01 7.656611e-02
#> [6] 3.677064e-01 1.951288e-02 1.178676e-01 4.430909e-01 2.201124e-01
#> [11] 7.512935e-01 8.802315e-01 4.345605e-04 1.089475e-02 4.838193e-03
#> [16] 4.345605e-04 1.254033e-01 3.998997e-01 5.340634e-01 5.797280e-02
#> [21] 4.995753e-01 7.263559e-01 2.948821e-01 3.150818e-01 5.797280e-02
#> [26] 3.464941e-01 8.280154e-01 7.138300e-01 3.976686e-02 2.863630e-02
#> [31] 1.657875e-01 5.156228e-02 6.892572e-01 7.512935e-01 1.570496e-01
#> [36] 3.150818e-01 9.727849e-01 2.863630e-02 8.933654e-01 5.340634e-01
#> [41] 7.015414e-02 9.459530e-01 2.566868e-01 4.544645e-01 2.013839e-01
#> [46] 2.754442e-01 8.328173e-02 8.411012e-01 6.407216e-01 9.013712e-02
#> [51] 2.294729e-01 4.995753e-01 1.254033e-01 5.808054e-01 7.512935e-01
#> [56] 8.670975e-01 9.013712e-02 9.727849e-01 6.167592e-01 1.835525e-01
#> [61] 1.746301e-01 3.998997e-01 3.677064e-01 1.951288e-02 2.294729e-01
#> [66] 6.528444e-01 3.998997e-01 3.577274e-05 6.649487e-01 2.948821e-01
#> [71] 9.194258e-01 5.340634e-01 5.688307e-01 7.894808e-01 7.894808e-01
#> [76] 1.037676e-01 5.224396e-01 3.464941e-01 4.544645e-01 1.254033e-01
#> [81] 1.486014e-01 7.894808e-01 3.677064e-01 7.263559e-01 8.411012e-01
#> [86] 2.754442e-01 2.566868e-01 3.998997e-01 6.046897e-01 8.933654e-01
#> [91] 1.835525e-01 3.357817e-01 9.593120e-01 4.880585e-01 3.976686e-02
#> [96] 2.294729e-01 4.544645e-01 9.194258e-01 2.107396e-01 5.808054e-01
#> [101] 6.892572e-01 6.167592e-01 4.838193e-03 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 194 69 166 177 128 100 175 170 39 40 159 149 164
#> 22.40 23.23 19.98 12.53 20.35 16.07 21.91 19.54 15.59 18.00 10.55 8.37 23.60
#> 169 92 164.1 55 125 133 32 18 107 111 30 32.1 192
#> 22.41 22.92 23.60 19.34 15.65 14.65 20.90 15.21 11.18 17.45 17.43 20.90 16.44
#> 145 43 197 136 179 139 56 159.1 97 30.1 127 136.1 70
#> 10.07 12.10 21.60 21.83 18.63 21.49 12.21 10.55 19.14 17.43 3.53 21.83 7.38
#> 133.1 190 25 184 167 108 117 150 187 14 158 134 18.1
#> 14.65 20.81 6.32 17.77 15.55 18.29 17.46 20.33 9.92 12.89 20.14 17.81 15.21
#> 58 81 159.2 183 158.1 127.1 123 88 8 125.1 100.1 175.1 134.1
#> 19.34 14.06 10.55 9.24 20.14 3.53 13.00 18.37 18.43 15.65 16.07 21.91 17.81
#> 154 125.2 86 177.1 111.1 77 133.2 57 10 10.1 166.1 157 85
#> 12.63 15.65 23.81 12.53 17.45 7.27 14.65 14.46 10.53 10.53 19.98 15.10 16.44
#> 167.1 55.1 76 10.2 100.2 107.1 187.1 117.1 184.1 125.3 60 70.1 88.1
#> 15.55 19.34 19.22 10.53 16.07 11.18 9.92 17.46 17.77 15.65 13.15 7.38 18.37
#> 45 91 29 197.1 134.2 167.2 77.1 41 81.1 56.1 123.1 92.1 28
#> 17.42 5.33 15.45 21.60 17.81 15.55 7.27 18.02 14.06 12.21 13.00 22.92 24.00
#> 138 102 198 75 193 112 31 19 11 27 120 7 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 141 135 7.1 62 198.1 7.2 137.1 147 147.1 44 176 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 165 38 151 27.1 138.1 173 120.1 178 144 74 156 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 2 141.1 28.1 163 162.1 173.1 135.1 74.1 71 143 44.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 3.1 19.1 173.2 94 74.2 118 62.1 27.2 119 182 191 135.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 46 119.1 138.2 165.1 143.1 21 138.3 163.1 62.2 141.2 172 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 74.3 87 17 44.2 74.4
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[7]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007935443 0.173244944 0.033337324
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.24033483 0.01933316 0.06590188
#> grade_iii, Cure model
#> 1.41292797
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 40 18.00 1 28 1 0
#> 179 18.63 1 42 0 0
#> 57 14.46 1 45 0 1
#> 114 13.68 1 NA 0 0
#> 114.1 13.68 1 NA 0 0
#> 150 20.33 1 48 0 0
#> 129 23.41 1 53 1 0
#> 5 16.43 1 51 0 1
#> 108 18.29 1 39 0 1
#> 124 9.73 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 23 16.92 1 61 0 0
#> 43 12.10 1 61 0 1
#> 140 12.68 1 59 1 0
#> 23.1 16.92 1 61 0 0
#> 130 16.47 1 53 0 1
#> 189 10.51 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 70 7.38 1 30 1 0
#> 10 10.53 1 34 0 0
#> 111 17.45 1 47 0 1
#> 81 14.06 1 34 0 0
#> 127 3.53 1 62 0 1
#> 140.1 12.68 1 59 1 0
#> 175 21.91 1 43 0 0
#> 50 10.02 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 175.1 21.91 1 43 0 0
#> 175.2 21.91 1 43 0 0
#> 158 20.14 1 74 1 0
#> 124.1 9.73 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 89 11.44 1 NA 0 0
#> 150.1 20.33 1 48 0 0
#> 195 11.76 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 194 22.40 1 38 0 1
#> 123 13.00 1 44 1 0
#> 140.2 12.68 1 59 1 0
#> 113 22.86 1 34 0 0
#> 60 13.15 1 38 1 0
#> 188 16.16 1 46 0 1
#> 92 22.92 1 47 0 1
#> 59 10.16 1 NA 1 0
#> 113.1 22.86 1 34 0 0
#> 123.1 13.00 1 44 1 0
#> 60.1 13.15 1 38 1 0
#> 111.1 17.45 1 47 0 1
#> 93 10.33 1 52 0 1
#> 85 16.44 1 36 0 0
#> 49 12.19 1 48 1 0
#> 58 19.34 1 39 0 0
#> 45 17.42 1 54 0 1
#> 86 23.81 1 58 0 1
#> 55 19.34 1 69 0 1
#> 187 9.92 1 39 1 0
#> 76 19.22 1 54 0 1
#> 159 10.55 1 50 0 1
#> 42 12.43 1 49 0 1
#> 61 10.12 1 36 0 1
#> 26 15.77 1 49 0 1
#> 90.1 20.94 1 50 0 1
#> 180 14.82 1 37 0 0
#> 41 18.02 1 40 1 0
#> 100 16.07 1 60 0 0
#> 155 13.08 1 26 0 0
#> 195.1 11.76 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 159.1 10.55 1 50 0 1
#> 89.1 11.44 1 NA 0 0
#> 153 21.33 1 55 1 0
#> 187.1 9.92 1 39 1 0
#> 153.1 21.33 1 55 1 0
#> 40.1 18.00 1 28 1 0
#> 30 17.43 1 78 0 0
#> 37 12.52 1 57 1 0
#> 177 12.53 1 75 0 0
#> 153.2 21.33 1 55 1 0
#> 96 14.54 1 33 0 1
#> 130.1 16.47 1 53 0 1
#> 166 19.98 1 48 0 0
#> 127.1 3.53 1 62 0 1
#> 199 19.81 1 NA 0 1
#> 18 15.21 1 49 1 0
#> 39 15.59 1 37 0 1
#> 166.1 19.98 1 48 0 0
#> 30.1 17.43 1 78 0 0
#> 111.2 17.45 1 47 0 1
#> 166.2 19.98 1 48 0 0
#> 42.1 12.43 1 49 0 1
#> 153.3 21.33 1 55 1 0
#> 86.1 23.81 1 58 0 1
#> 164 23.60 1 76 0 1
#> 153.4 21.33 1 55 1 0
#> 124.2 9.73 1 NA 1 0
#> 153.5 21.33 1 55 1 0
#> 23.2 16.92 1 61 0 0
#> 77 7.27 1 67 0 1
#> 197 21.60 1 69 1 0
#> 5.1 16.43 1 51 0 1
#> 39.1 15.59 1 37 0 1
#> 114.2 13.68 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 76.1 19.22 1 54 0 1
#> 6 15.64 1 39 0 0
#> 32 20.90 1 37 1 0
#> 154 12.63 1 20 1 0
#> 92.1 22.92 1 47 0 1
#> 188.1 16.16 1 46 0 1
#> 88 18.37 1 47 0 0
#> 6.1 15.64 1 39 0 0
#> 42.2 12.43 1 49 0 1
#> 9 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 33 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 87 24.00 0 27 0 0
#> 160 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 165 24.00 0 47 0 0
#> 200 24.00 0 64 0 0
#> 54 24.00 0 53 1 0
#> 71 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 38 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 141.1 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 162 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 83.1 24.00 0 6 0 0
#> 162.1 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 162.2 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 138 24.00 0 44 1 0
#> 162.3 24.00 0 51 0 0
#> 102.1 24.00 0 49 0 0
#> 3 24.00 0 31 1 0
#> 148.1 24.00 0 61 1 0
#> 173 24.00 0 19 0 1
#> 173.1 24.00 0 19 0 1
#> 146 24.00 0 63 1 0
#> 62 24.00 0 71 0 0
#> 98 24.00 0 34 1 0
#> 34 24.00 0 36 0 0
#> 72 24.00 0 40 0 1
#> 174 24.00 0 49 1 0
#> 147 24.00 0 76 1 0
#> 161 24.00 0 45 0 0
#> 120 24.00 0 68 0 1
#> 54.1 24.00 0 53 1 0
#> 182 24.00 0 35 0 0
#> 112 24.00 0 61 0 0
#> 160.1 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 160.2 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 138.1 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 138.2 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 178 24.00 0 52 1 0
#> 33.1 24.00 0 53 0 0
#> 72.1 24.00 0 40 0 1
#> 72.2 24.00 0 40 0 1
#> 84 24.00 0 39 0 1
#> 126 24.00 0 48 0 0
#> 196 24.00 0 19 0 0
#> 102.2 24.00 0 49 0 0
#> 34.1 24.00 0 36 0 0
#> 104 24.00 0 50 1 0
#> 47 24.00 0 38 0 1
#> 73 24.00 0 NA 0 1
#> 20.1 24.00 0 46 1 0
#> 17 24.00 0 38 0 1
#> 147.1 24.00 0 76 1 0
#> 65 24.00 0 57 1 0
#> 118.1 24.00 0 44 1 0
#> 7.1 24.00 0 37 1 0
#> 12.1 24.00 0 63 0 0
#> 137 24.00 0 45 1 0
#> 143 24.00 0 51 0 0
#> 47.1 24.00 0 38 0 1
#> 48 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 173.2 24.00 0 19 0 1
#> 161.1 24.00 0 45 0 0
#> 152 24.00 0 36 0 1
#> 80 24.00 0 41 0 0
#> 118.2 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 109.1 24.00 0 48 0 0
#> 53 24.00 0 32 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.24 NA NA NA
#> 2 age, Cure model 0.0193 NA NA NA
#> 3 grade_ii, Cure model 0.0659 NA NA NA
#> 4 grade_iii, Cure model 1.41 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00794 NA NA NA
#> 2 grade_ii, Survival model 0.173 NA NA NA
#> 3 grade_iii, Survival model 0.0333 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.24033 0.01933 0.06590 1.41293
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.8
#> Residual Deviance: 236.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.24033483 0.01933316 0.06590188 1.41292797
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007935443 0.173244944 0.033337324
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.293570042 0.244169420 0.619575189 0.147829495 0.011107927 0.463764092
#> [7] 0.263600575 0.016196465 0.396858178 0.836847803 0.707532689 0.396858178
#> [13] 0.429705553 0.323670235 0.944880454 0.876948286 0.333947802 0.632078247
#> [19] 0.972356109 0.707532689 0.050674061 0.124026919 0.050674061 0.050674061
#> [25] 0.164188493 0.273462311 0.147829495 0.116235028 0.044115882 0.682296082
#> [31] 0.707532689 0.032355015 0.644640071 0.486823854 0.021553837 0.032355015
#> [37] 0.682296082 0.644640071 0.333947802 0.890475241 0.452266919 0.823572614
#> [43] 0.198256260 0.385949269 0.001405750 0.198256260 0.917705238 0.216187727
#> [49] 0.850199846 0.784501738 0.904067374 0.522124225 0.124026919 0.594759687
#> [55] 0.283492225 0.510196293 0.669635193 0.313444270 0.850199846 0.077167771
#> [61] 0.917705238 0.077167771 0.293570042 0.364633675 0.771453587 0.758458962
#> [67] 0.077167771 0.607141533 0.429705553 0.172730667 0.972356109 0.582443088
#> [73] 0.558168843 0.172730667 0.364633675 0.333947802 0.172730667 0.784501738
#> [79] 0.077167771 0.001405750 0.006508434 0.077167771 0.077167771 0.396858178
#> [85] 0.958579646 0.069849180 0.463764092 0.558168843 0.234618846 0.216187727
#> [91] 0.534134251 0.139704273 0.745563436 0.021553837 0.486823854 0.253827099
#> [97] 0.534134251 0.784501738 0.000000000 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 40 179 57 150 129 5 108 69 23 43 140 23.1 130
#> 18.00 18.63 14.46 20.33 23.41 16.43 18.29 23.23 16.92 12.10 12.68 16.92 16.47
#> 117 70 10 111 81 127 140.1 175 90 175.1 175.2 158 51
#> 17.46 7.38 10.53 17.45 14.06 3.53 12.68 21.91 20.94 21.91 21.91 20.14 18.23
#> 150.1 99 194 123 140.2 113 60 188 92 113.1 123.1 60.1 111.1
#> 20.33 21.19 22.40 13.00 12.68 22.86 13.15 16.16 22.92 22.86 13.00 13.15 17.45
#> 93 85 49 58 45 86 55 187 76 159 42 61 26
#> 10.33 16.44 12.19 19.34 17.42 23.81 19.34 9.92 19.22 10.55 12.43 10.12 15.77
#> 90.1 180 41 100 155 110 159.1 153 187.1 153.1 40.1 30 37
#> 20.94 14.82 18.02 16.07 13.08 17.56 10.55 21.33 9.92 21.33 18.00 17.43 12.52
#> 177 153.2 96 130.1 166 127.1 18 39 166.1 30.1 111.2 166.2 42.1
#> 12.53 21.33 14.54 16.47 19.98 3.53 15.21 15.59 19.98 17.43 17.45 19.98 12.43
#> 153.3 86.1 164 153.4 153.5 23.2 77 197 5.1 39.1 97 76.1 6
#> 21.33 23.81 23.60 21.33 21.33 16.92 7.27 21.60 16.43 15.59 19.14 19.22 15.64
#> 32 154 92.1 188.1 88 6.1 42.2 9 28 33 148 87 160
#> 20.90 12.63 22.92 16.16 18.37 15.64 12.43 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 20 165 200 54 71 12 38 131 141 109 141.1 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 83 83.1 162.1 122 162.2 7 138 162.3 102.1 3 148.1 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.1 146 62 98 34 72 174 147 161 120 54.1 182 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1 21 121 35 118 160.2 142 138.1 163 138.2 116 178 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 72.2 84 126 196 102.2 34.1 104 47 20.1 17 147.1 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118.1 7.1 12.1 137 143 47.1 48 19 173.2 161.1 152 80 118.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 109.1 53
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[8]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001289253 0.564392350 0.399953062
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.0167859016 0.0003424235 -0.4253214341
#> grade_iii, Cure model
#> 0.8825953392
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 29 15.45 1 68 1 0
#> 30 17.43 1 78 0 0
#> 111 17.45 1 47 0 1
#> 60 13.15 1 38 1 0
#> 190 20.81 1 42 1 0
#> 57 14.46 1 45 0 1
#> 134 17.81 1 47 1 0
#> 183 9.24 1 67 1 0
#> 15 22.68 1 48 0 0
#> 90 20.94 1 50 0 1
#> 37 12.52 1 57 1 0
#> 124 9.73 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 190.1 20.81 1 42 1 0
#> 136 21.83 1 43 0 1
#> 154 12.63 1 20 1 0
#> 181 16.46 1 45 0 1
#> 190.2 20.81 1 42 1 0
#> 90.1 20.94 1 50 0 1
#> 155 13.08 1 26 0 0
#> 50 10.02 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 30.1 17.43 1 78 0 0
#> 117 17.46 1 26 0 1
#> 170 19.54 1 43 0 1
#> 15.1 22.68 1 48 0 0
#> 154.1 12.63 1 20 1 0
#> 139 21.49 1 63 1 0
#> 150 20.33 1 48 0 0
#> 13 14.34 1 54 0 1
#> 108 18.29 1 39 0 1
#> 55 19.34 1 69 0 1
#> 111.1 17.45 1 47 0 1
#> 43 12.10 1 61 0 1
#> 90.2 20.94 1 50 0 1
#> 43.1 12.10 1 61 0 1
#> 77 7.27 1 67 0 1
#> 24 23.89 1 38 0 0
#> 183.1 9.24 1 67 1 0
#> 13.1 14.34 1 54 0 1
#> 6 15.64 1 39 0 0
#> 166 19.98 1 48 0 0
#> 97 19.14 1 65 0 1
#> 59 10.16 1 NA 1 0
#> 190.3 20.81 1 42 1 0
#> 88 18.37 1 47 0 0
#> 113 22.86 1 34 0 0
#> 89 11.44 1 NA 0 0
#> 183.2 9.24 1 67 1 0
#> 51.1 18.23 1 83 0 1
#> 195 11.76 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 13.2 14.34 1 54 0 1
#> 99 21.19 1 38 0 1
#> 150.1 20.33 1 48 0 0
#> 36 21.19 1 48 0 1
#> 179 18.63 1 42 0 0
#> 129 23.41 1 53 1 0
#> 164 23.60 1 76 0 1
#> 45 17.42 1 54 0 1
#> 76 19.22 1 54 0 1
#> 101 9.97 1 10 0 1
#> 133 14.65 1 57 0 0
#> 10 10.53 1 34 0 0
#> 169 22.41 1 46 0 0
#> 25 6.32 1 34 1 0
#> 10.1 10.53 1 34 0 0
#> 42 12.43 1 49 0 1
#> 199 19.81 1 NA 0 1
#> 124.1 9.73 1 NA 1 0
#> 55.1 19.34 1 69 0 1
#> 45.1 17.42 1 54 0 1
#> 133.1 14.65 1 57 0 0
#> 24.1 23.89 1 38 0 0
#> 57.1 14.46 1 45 0 1
#> 8 18.43 1 32 0 0
#> 96 14.54 1 33 0 1
#> 41 18.02 1 40 1 0
#> 168 23.72 1 70 0 0
#> 42.1 12.43 1 49 0 1
#> 108.1 18.29 1 39 0 1
#> 133.2 14.65 1 57 0 0
#> 175 21.91 1 43 0 0
#> 117.1 17.46 1 26 0 1
#> 58 19.34 1 39 0 0
#> 86 23.81 1 58 0 1
#> 123 13.00 1 44 1 0
#> 81 14.06 1 34 0 0
#> 133.3 14.65 1 57 0 0
#> 145 10.07 1 65 1 0
#> 58.1 19.34 1 39 0 0
#> 58.2 19.34 1 39 0 0
#> 63 22.77 1 31 1 0
#> 69 23.23 1 25 0 1
#> 154.2 12.63 1 20 1 0
#> 127 3.53 1 62 0 1
#> 4 17.64 1 NA 0 1
#> 4.1 17.64 1 NA 0 1
#> 13.3 14.34 1 54 0 1
#> 167 15.55 1 56 1 0
#> 40 18.00 1 28 1 0
#> 14 12.89 1 21 0 0
#> 39 15.59 1 37 0 1
#> 153 21.33 1 55 1 0
#> 41.1 18.02 1 40 1 0
#> 37.1 12.52 1 57 1 0
#> 97.1 19.14 1 65 0 1
#> 68 20.62 1 44 0 0
#> 93 10.33 1 52 0 1
#> 26 15.77 1 49 0 1
#> 39.1 15.59 1 37 0 1
#> 184 17.77 1 38 0 0
#> 109 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 152 24.00 0 36 0 1
#> 156 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 9 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 186 24.00 0 45 1 0
#> 147 24.00 0 76 1 0
#> 47 24.00 0 38 0 1
#> 104 24.00 0 50 1 0
#> 137 24.00 0 45 1 0
#> 137.1 24.00 0 45 1 0
#> 33 24.00 0 53 0 0
#> 138.1 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 135 24.00 0 58 1 0
#> 161 24.00 0 45 0 0
#> 3 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 146 24.00 0 63 1 0
#> 103.1 24.00 0 56 1 0
#> 148 24.00 0 61 1 0
#> 160.1 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 186.1 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#> 186.2 24.00 0 45 1 0
#> 152.1 24.00 0 36 0 1
#> 138.2 24.00 0 44 1 0
#> 152.2 24.00 0 36 0 1
#> 82 24.00 0 34 0 0
#> 75 24.00 0 21 1 0
#> 38 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 176 24.00 0 43 0 1
#> 95.1 24.00 0 68 0 1
#> 121 24.00 0 57 1 0
#> 141.1 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 126 24.00 0 48 0 0
#> 27 24.00 0 63 1 0
#> 144 24.00 0 28 0 1
#> 122.1 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 176.1 24.00 0 43 0 1
#> 35 24.00 0 51 0 0
#> 141.2 24.00 0 44 1 0
#> 35.1 24.00 0 51 0 0
#> 172.1 24.00 0 41 0 0
#> 80 24.00 0 41 0 0
#> 19.1 24.00 0 57 0 1
#> 19.2 24.00 0 57 0 1
#> 163 24.00 0 66 0 0
#> 35.2 24.00 0 51 0 0
#> 137.2 24.00 0 45 1 0
#> 148.1 24.00 0 61 1 0
#> 193 24.00 0 45 0 1
#> 174 24.00 0 49 1 0
#> 28 24.00 0 67 1 0
#> 48 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 95.2 24.00 0 68 0 1
#> 122.2 24.00 0 66 0 0
#> 109.1 24.00 0 48 0 0
#> 132 24.00 0 55 0 0
#> 47.1 24.00 0 38 0 1
#> 196 24.00 0 19 0 0
#> 161.1 24.00 0 45 0 0
#> 48.1 24.00 0 31 1 0
#> 38.1 24.00 0 31 1 0
#> 98.1 24.00 0 34 1 0
#> 131 24.00 0 66 0 0
#> 9.1 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 103.2 24.00 0 56 1 0
#> 122.3 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 53 24.00 0 32 0 1
#> 84 24.00 0 39 0 1
#> 112 24.00 0 61 0 0
#> 186.3 24.00 0 45 1 0
#> 102 24.00 0 49 0 0
#> 71 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0168 NA NA NA
#> 2 age, Cure model 0.000342 NA NA NA
#> 3 grade_ii, Cure model -0.425 NA NA NA
#> 4 grade_iii, Cure model 0.883 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00129 NA NA NA
#> 2 grade_ii, Survival model 0.564 NA NA NA
#> 3 grade_iii, Survival model 0.400 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.0167859 0.0003424 -0.4253214 0.8825953
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 250.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.0167859016 0.0003424235 -0.4253214341 0.8825953392
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001289253 0.564392350 0.399953062
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.70539805 0.62075056 0.60360980 0.81043488 0.31358357 0.75449353
#> [7] 0.56857339 0.94873672 0.15693694 0.28190074 0.86539669 0.19609410
#> [13] 0.31358357 0.22222101 0.84227319 0.65494363 0.31358357 0.28190074
#> [19] 0.81841738 0.52337618 0.62075056 0.58627014 0.39146374 0.15693694
#> [25] 0.84227319 0.23499746 0.36171855 0.77074855 0.50482132 0.40137243
#> [31] 0.60360980 0.89591387 0.28190074 0.89591387 0.97809587 0.01704981
#> [37] 0.94873672 0.77074855 0.67192813 0.38145083 0.45753576 0.31358357
#> [43] 0.49530936 0.12942151 0.94873672 0.52337618 0.97074275 0.77074855
#> [49] 0.25933438 0.36171855 0.25933438 0.47631442 0.10032453 0.08379625
#> [55] 0.63793675 0.44789952 0.94123648 0.71366109 0.91102237 0.18267813
#> [61] 0.98542869 0.91102237 0.88070820 0.40137243 0.63793675 0.71366109
#> [67] 0.01704981 0.75449353 0.48580814 0.74624896 0.54170991 0.06605096
#> [73] 0.88070820 0.50482132 0.71366109 0.20913543 0.58627014 0.40137243
#> [79] 0.04873272 0.82640245 0.80239900 0.71366109 0.93370788 0.40137243
#> [85] 0.40137243 0.14363217 0.11527893 0.84227319 0.99272443 0.77074855
#> [91] 0.69707547 0.55963721 0.83433681 0.68040386 0.24735674 0.54170991
#> [97] 0.86539669 0.45753576 0.35174729 0.92614163 0.66345764 0.68040386
#> [103] 0.57741852 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 29 30 111 60 190 57 134 183 15 90 37 194 190.1
#> 15.45 17.43 17.45 13.15 20.81 14.46 17.81 9.24 22.68 20.94 12.52 22.40 20.81
#> 136 154 181 190.2 90.1 155 51 30.1 117 170 15.1 154.1 139
#> 21.83 12.63 16.46 20.81 20.94 13.08 18.23 17.43 17.46 19.54 22.68 12.63 21.49
#> 150 13 108 55 111.1 43 90.2 43.1 77 24 183.1 13.1 6
#> 20.33 14.34 18.29 19.34 17.45 12.10 20.94 12.10 7.27 23.89 9.24 14.34 15.64
#> 166 97 190.3 88 113 183.2 51.1 149 13.2 99 150.1 36 179
#> 19.98 19.14 20.81 18.37 22.86 9.24 18.23 8.37 14.34 21.19 20.33 21.19 18.63
#> 129 164 45 76 101 133 10 169 25 10.1 42 55.1 45.1
#> 23.41 23.60 17.42 19.22 9.97 14.65 10.53 22.41 6.32 10.53 12.43 19.34 17.42
#> 133.1 24.1 57.1 8 96 41 168 42.1 108.1 133.2 175 117.1 58
#> 14.65 23.89 14.46 18.43 14.54 18.02 23.72 12.43 18.29 14.65 21.91 17.46 19.34
#> 86 123 81 133.3 145 58.1 58.2 63 69 154.2 127 13.3 167
#> 23.81 13.00 14.06 14.65 10.07 19.34 19.34 22.77 23.23 12.63 3.53 14.34 15.55
#> 40 14 39 153 41.1 37.1 97.1 68 93 26 39.1 184 109
#> 18.00 12.89 15.59 21.33 18.02 12.52 19.14 20.62 10.33 15.77 15.59 17.77 24.00
#> 141 138 160 172 152 156 103 9 122 98 186 147 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 137 137.1 33 138.1 19 135 161 3 33.1 146 103.1 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1 87 186.1 95 186.2 152.1 138.2 152.2 82 75 38 198 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.1 121 141.1 151 126 27 144 122.1 1 176.1 35 141.2 35.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 80 19.1 19.2 163 35.2 137.2 148.1 193 174 28 48 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.2 122.2 109.1 132 47.1 196 161.1 48.1 38.1 98.1 131 9.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.2 122.3 21 53 84 112 186.3 102 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[9]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007895424 0.970360170 1.307794463
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.05824052 0.02090246 0.08327502
#> grade_iii, Cure model
#> 1.04802521
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 40 18.00 1 28 1 0
#> 10 10.53 1 34 0 0
#> 40.1 18.00 1 28 1 0
#> 168 23.72 1 70 0 0
#> 18 15.21 1 49 1 0
#> 42 12.43 1 49 0 1
#> 130 16.47 1 53 0 1
#> 189 10.51 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 57 14.46 1 45 0 1
#> 114 13.68 1 NA 0 0
#> 30 17.43 1 78 0 0
#> 32 20.90 1 37 1 0
#> 129 23.41 1 53 1 0
#> 130.1 16.47 1 53 0 1
#> 168.1 23.72 1 70 0 0
#> 78 23.88 1 43 0 0
#> 24 23.89 1 38 0 0
#> 100 16.07 1 60 0 0
#> 90 20.94 1 50 0 1
#> 56 12.21 1 60 0 0
#> 136 21.83 1 43 0 1
#> 41 18.02 1 40 1 0
#> 140 12.68 1 59 1 0
#> 32.1 20.90 1 37 1 0
#> 179 18.63 1 42 0 0
#> 25 6.32 1 34 1 0
#> 130.2 16.47 1 53 0 1
#> 18.1 15.21 1 49 1 0
#> 24.1 23.89 1 38 0 0
#> 113 22.86 1 34 0 0
#> 111 17.45 1 47 0 1
#> 140.1 12.68 1 59 1 0
#> 58 19.34 1 39 0 0
#> 6 15.64 1 39 0 0
#> 181 16.46 1 45 0 1
#> 57.1 14.46 1 45 0 1
#> 139 21.49 1 63 1 0
#> 117 17.46 1 26 0 1
#> 76 19.22 1 54 0 1
#> 101 9.97 1 10 0 1
#> 154 12.63 1 20 1 0
#> 61 10.12 1 36 0 1
#> 101.1 9.97 1 10 0 1
#> 130.3 16.47 1 53 0 1
#> 14 12.89 1 21 0 0
#> 183 9.24 1 67 1 0
#> 6.1 15.64 1 39 0 0
#> 43 12.10 1 61 0 1
#> 60 13.15 1 38 1 0
#> 4 17.64 1 NA 0 1
#> 140.2 12.68 1 59 1 0
#> 55 19.34 1 69 0 1
#> 155 13.08 1 26 0 0
#> 168.2 23.72 1 70 0 0
#> 153 21.33 1 55 1 0
#> 29 15.45 1 68 1 0
#> 170 19.54 1 43 0 1
#> 55.1 19.34 1 69 0 1
#> 145 10.07 1 65 1 0
#> 40.2 18.00 1 28 1 0
#> 113.1 22.86 1 34 0 0
#> 13 14.34 1 54 0 1
#> 192 16.44 1 31 1 0
#> 68 20.62 1 44 0 0
#> 127 3.53 1 62 0 1
#> 194 22.40 1 38 0 1
#> 158 20.14 1 74 1 0
#> 61.1 10.12 1 36 0 1
#> 97 19.14 1 65 0 1
#> 107 11.18 1 54 1 0
#> 42.1 12.43 1 49 0 1
#> 113.2 22.86 1 34 0 0
#> 93 10.33 1 52 0 1
#> 125 15.65 1 67 1 0
#> 42.2 12.43 1 49 0 1
#> 61.2 10.12 1 36 0 1
#> 168.3 23.72 1 70 0 0
#> 125.1 15.65 1 67 1 0
#> 177 12.53 1 75 0 0
#> 124 9.73 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 91 5.33 1 61 0 1
#> 96 14.54 1 33 0 1
#> 52 10.42 1 52 0 1
#> 88 18.37 1 47 0 0
#> 108 18.29 1 39 0 1
#> 26 15.77 1 49 0 1
#> 179.1 18.63 1 42 0 0
#> 40.3 18.00 1 28 1 0
#> 175 21.91 1 43 0 0
#> 43.1 12.10 1 61 0 1
#> 179.2 18.63 1 42 0 0
#> 153.1 21.33 1 55 1 0
#> 175.1 21.91 1 43 0 0
#> 40.4 18.00 1 28 1 0
#> 15 22.68 1 48 0 0
#> 26.1 15.77 1 49 0 1
#> 133 14.65 1 57 0 0
#> 57.2 14.46 1 45 0 1
#> 177.1 12.53 1 75 0 0
#> 110.1 17.56 1 65 0 1
#> 88.1 18.37 1 47 0 0
#> 187 9.92 1 39 1 0
#> 168.4 23.72 1 70 0 0
#> 30.1 17.43 1 78 0 0
#> 197 21.60 1 69 1 0
#> 197.1 21.60 1 69 1 0
#> 70 7.38 1 30 1 0
#> 150 20.33 1 48 0 0
#> 127.1 3.53 1 62 0 1
#> 50 10.02 1 NA 1 0
#> 151 24.00 0 42 0 0
#> 109 24.00 0 48 0 0
#> 34 24.00 0 36 0 0
#> 67 24.00 0 25 0 0
#> 48 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 103 24.00 0 56 1 0
#> 163 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 137 24.00 0 45 1 0
#> 161 24.00 0 45 0 0
#> 131 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 82 24.00 0 34 0 0
#> 163.1 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 11 24.00 0 42 0 1
#> 71 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 116 24.00 0 58 0 1
#> 83.1 24.00 0 6 0 0
#> 102 24.00 0 49 0 0
#> 174 24.00 0 49 1 0
#> 87 24.00 0 27 0 0
#> 141 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 83.2 24.00 0 6 0 0
#> 3 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 53 24.00 0 32 0 1
#> 146.1 24.00 0 63 1 0
#> 186 24.00 0 45 1 0
#> 67.1 24.00 0 25 0 0
#> 161.2 24.00 0 45 0 0
#> 191 24.00 0 60 0 1
#> 138 24.00 0 44 1 0
#> 48.1 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 161.3 24.00 0 45 0 0
#> 182 24.00 0 35 0 0
#> 98 24.00 0 34 1 0
#> 33 24.00 0 53 0 0
#> 146.2 24.00 0 63 1 0
#> 82.1 24.00 0 34 0 0
#> 87.1 24.00 0 27 0 0
#> 72 24.00 0 40 0 1
#> 126.1 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 160 24.00 0 31 1 0
#> 102.1 24.00 0 49 0 0
#> 122 24.00 0 66 0 0
#> 7 24.00 0 37 1 0
#> 152 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 119 24.00 0 17 0 0
#> 115 24.00 0 NA 1 0
#> 103.1 24.00 0 56 1 0
#> 191.1 24.00 0 60 0 1
#> 120 24.00 0 68 0 1
#> 138.1 24.00 0 44 1 0
#> 137.1 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 143 24.00 0 51 0 0
#> 174.1 24.00 0 49 1 0
#> 53.1 24.00 0 32 0 1
#> 119.1 24.00 0 17 0 0
#> 135 24.00 0 58 1 0
#> 84 24.00 0 39 0 1
#> 173 24.00 0 19 0 1
#> 73 24.00 0 NA 0 1
#> 138.2 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 138.3 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 20 24.00 0 46 1 0
#> 120.1 24.00 0 68 0 1
#> 82.2 24.00 0 34 0 0
#> 28.1 24.00 0 67 1 0
#> 126.2 24.00 0 48 0 0
#> 148 24.00 0 61 1 0
#> 95 24.00 0 68 0 1
#> 143.1 24.00 0 51 0 0
#> 191.2 24.00 0 60 0 1
#> 75.1 24.00 0 21 1 0
#> 75.2 24.00 0 21 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.06 NA NA NA
#> 2 age, Cure model 0.0209 NA NA NA
#> 3 grade_ii, Cure model 0.0833 NA NA NA
#> 4 grade_iii, Cure model 1.05 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00790 NA NA NA
#> 2 grade_ii, Survival model 0.970 NA NA NA
#> 3 grade_iii, Survival model 1.31 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05824 0.02090 0.08328 1.04803
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.3
#> Residual Deviance: 251 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05824052 0.02090246 0.08327502 1.04802521
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007895424 0.970360170 1.307794463
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.552143994 0.908248386 0.552143994 0.040172534 0.750566206 0.864613329
#> [7] 0.646372902 0.192088631 0.779013884 0.629750496 0.358565910 0.107687204
#> [13] 0.646372902 0.040172534 0.025465821 0.006602465 0.692157028 0.345921377
#> [19] 0.883385451 0.261275449 0.542216960 0.825688867 0.358565910 0.481131593
#> [25] 0.978088351 0.646372902 0.750566206 0.006602465 0.124727553 0.621484717
#> [31] 0.825688867 0.429055257 0.728789843 0.676964492 0.779013884 0.305449432
#> [37] 0.613044775 0.460577895 0.949934747 0.845150256 0.926624057 0.949934747
#> [43] 0.646372902 0.819046547 0.966881326 0.728789843 0.889704691 0.805788387
#> [49] 0.825688867 0.429055257 0.812412448 0.040172534 0.319691058 0.743309314
#> [55] 0.417702532 0.429055257 0.944095604 0.552143994 0.124727553 0.799111918
#> [61] 0.684605681 0.381845142 0.989155885 0.211318700 0.405822444 0.926624057
#> [67] 0.470990770 0.902073396 0.864613329 0.124727553 0.920557983 0.714346639
#> [73] 0.864613329 0.926624057 0.040172534 0.714346639 0.851625049 0.595806991
#> [79] 0.983642113 0.771963981 0.914433276 0.511447476 0.532119064 0.699739589
#> [85] 0.481131593 0.552143994 0.227922922 0.889704691 0.481131593 0.319691058
#> [91] 0.227922922 0.552143994 0.173428528 0.699739589 0.764792938 0.779013884
#> [97] 0.851625049 0.595806991 0.511447476 0.961242152 0.040172534 0.629750496
#> [103] 0.276843299 0.276843299 0.972502311 0.393776216 0.989155885 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000
#>
#> $Time
#> 40 10 40.1 168 18 42 130 169 57 30 32 129 130.1
#> 18.00 10.53 18.00 23.72 15.21 12.43 16.47 22.41 14.46 17.43 20.90 23.41 16.47
#> 168.1 78 24 100 90 56 136 41 140 32.1 179 25 130.2
#> 23.72 23.88 23.89 16.07 20.94 12.21 21.83 18.02 12.68 20.90 18.63 6.32 16.47
#> 18.1 24.1 113 111 140.1 58 6 181 57.1 139 117 76 101
#> 15.21 23.89 22.86 17.45 12.68 19.34 15.64 16.46 14.46 21.49 17.46 19.22 9.97
#> 154 61 101.1 130.3 14 183 6.1 43 60 140.2 55 155 168.2
#> 12.63 10.12 9.97 16.47 12.89 9.24 15.64 12.10 13.15 12.68 19.34 13.08 23.72
#> 153 29 170 55.1 145 40.2 113.1 13 192 68 127 194 158
#> 21.33 15.45 19.54 19.34 10.07 18.00 22.86 14.34 16.44 20.62 3.53 22.40 20.14
#> 61.1 97 107 42.1 113.2 93 125 42.2 61.2 168.3 125.1 177 110
#> 10.12 19.14 11.18 12.43 22.86 10.33 15.65 12.43 10.12 23.72 15.65 12.53 17.56
#> 91 96 52 88 108 26 179.1 40.3 175 43.1 179.2 153.1 175.1
#> 5.33 14.54 10.42 18.37 18.29 15.77 18.63 18.00 21.91 12.10 18.63 21.33 21.91
#> 40.4 15 26.1 133 57.2 177.1 110.1 88.1 187 168.4 30.1 197 197.1
#> 18.00 22.68 15.77 14.65 14.46 12.53 17.56 18.37 9.92 23.72 17.43 21.60 21.60
#> 70 150 127.1 151 109 34 67 48 126 103 163 22 137
#> 7.38 20.33 3.53 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 131 146 82 163.1 172 47 83 11 71 28 116 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 174 87 141 35 83.2 3 161.1 53 146.1 186 67.1 161.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 138 48.1 118 161.3 182 98 33 146.2 82.1 87.1 72 126.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 75 160 102.1 122 7 152 132 119 103.1 191.1 120 138.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 165 143 174.1 53.1 119.1 135 84 173 138.2 112 138.3 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 120.1 82.2 28.1 126.2 148 95 143.1 191.2 75.1 75.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[10]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.008352158 0.297604632 0.268869092
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.72176478 0.01654259 -0.37190058
#> grade_iii, Cure model
#> 0.85261986
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 150 20.33 1 48 0 0
#> 189 10.51 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 123 13.00 1 44 1 0
#> 78 23.88 1 43 0 0
#> 85 16.44 1 36 0 0
#> 68 20.62 1 44 0 0
#> 113 22.86 1 34 0 0
#> 15 22.68 1 48 0 0
#> 107 11.18 1 54 1 0
#> 32 20.90 1 37 1 0
#> 89 11.44 1 NA 0 0
#> 105 19.75 1 60 0 0
#> 39 15.59 1 37 0 1
#> 52 10.42 1 52 0 1
#> 97 19.14 1 65 0 1
#> 13 14.34 1 54 0 1
#> 58 19.34 1 39 0 0
#> 167 15.55 1 56 1 0
#> 16 8.71 1 71 0 1
#> 15.1 22.68 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 145 10.07 1 65 1 0
#> 128 20.35 1 35 0 1
#> 199 19.81 1 NA 0 1
#> 69 23.23 1 25 0 1
#> 39.1 15.59 1 37 0 1
#> 26 15.77 1 49 0 1
#> 16.1 8.71 1 71 0 1
#> 61 10.12 1 36 0 1
#> 88 18.37 1 47 0 0
#> 139 21.49 1 63 1 0
#> 127 3.53 1 62 0 1
#> 108 18.29 1 39 0 1
#> 76 19.22 1 54 0 1
#> 39.2 15.59 1 37 0 1
#> 169 22.41 1 46 0 0
#> 101 9.97 1 10 0 1
#> 93 10.33 1 52 0 1
#> 77 7.27 1 67 0 1
#> 189.1 10.51 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 113.1 22.86 1 34 0 0
#> 134 17.81 1 47 1 0
#> 189.2 10.51 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 124 9.73 1 NA 1 0
#> 69.1 23.23 1 25 0 1
#> 78.1 23.88 1 43 0 0
#> 5 16.43 1 51 0 1
#> 58.1 19.34 1 39 0 0
#> 26.1 15.77 1 49 0 1
#> 105.1 19.75 1 60 0 0
#> 154 12.63 1 20 1 0
#> 68.1 20.62 1 44 0 0
#> 180 14.82 1 37 0 0
#> 100 16.07 1 60 0 0
#> 164 23.60 1 76 0 1
#> 179 18.63 1 42 0 0
#> 66 22.13 1 53 0 0
#> 56 12.21 1 60 0 0
#> 18 15.21 1 49 1 0
#> 39.3 15.59 1 37 0 1
#> 36 21.19 1 48 0 1
#> 63 22.77 1 31 1 0
#> 145.1 10.07 1 65 1 0
#> 194 22.40 1 38 0 1
#> 100.1 16.07 1 60 0 0
#> 86 23.81 1 58 0 1
#> 39.4 15.59 1 37 0 1
#> 69.2 23.23 1 25 0 1
#> 129 23.41 1 53 1 0
#> 136 21.83 1 43 0 1
#> 105.2 19.75 1 60 0 0
#> 63.1 22.77 1 31 1 0
#> 14 12.89 1 21 0 0
#> 145.2 10.07 1 65 1 0
#> 187 9.92 1 39 1 0
#> 8 18.43 1 32 0 0
#> 25 6.32 1 34 1 0
#> 177 12.53 1 75 0 0
#> 106 16.67 1 49 1 0
#> 96 14.54 1 33 0 1
#> 140 12.68 1 59 1 0
#> 77.1 7.27 1 67 0 1
#> 45 17.42 1 54 0 1
#> 130 16.47 1 53 0 1
#> 79 16.23 1 54 1 0
#> 183 9.24 1 67 1 0
#> 140.1 12.68 1 59 1 0
#> 129.1 23.41 1 53 1 0
#> 184 17.77 1 38 0 0
#> 105.3 19.75 1 60 0 0
#> 157 15.10 1 47 0 0
#> 96.1 14.54 1 33 0 1
#> 23 16.92 1 61 0 0
#> 133 14.65 1 57 0 0
#> 171 16.57 1 41 0 1
#> 181 16.46 1 45 0 1
#> 76.1 19.22 1 54 0 1
#> 99 21.19 1 38 0 1
#> 32.1 20.90 1 37 1 0
#> 40 18.00 1 28 1 0
#> 129.2 23.41 1 53 1 0
#> 81 14.06 1 34 0 0
#> 66.1 22.13 1 53 0 0
#> 89.1 11.44 1 NA 0 0
#> 86.1 23.81 1 58 0 1
#> 96.2 14.54 1 33 0 1
#> 159 10.55 1 50 0 1
#> 194.1 22.40 1 38 0 1
#> 134.1 17.81 1 47 1 0
#> 31 24.00 0 36 0 1
#> 142 24.00 0 53 0 0
#> 34 24.00 0 36 0 0
#> 131 24.00 0 66 0 0
#> 152 24.00 0 36 0 1
#> 161 24.00 0 45 0 0
#> 156 24.00 0 50 1 0
#> 156.1 24.00 0 50 1 0
#> 172 24.00 0 41 0 0
#> 2 24.00 0 9 0 0
#> 174 24.00 0 49 1 0
#> 160 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 131.1 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 142.1 24.00 0 53 0 0
#> 160.1 24.00 0 31 1 0
#> 118.1 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 118.2 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 64 24.00 0 43 0 0
#> 151 24.00 0 42 0 0
#> 162 24.00 0 51 0 0
#> 34.1 24.00 0 36 0 0
#> 116 24.00 0 58 0 1
#> 94 24.00 0 51 0 1
#> 148 24.00 0 61 1 0
#> 62.1 24.00 0 71 0 0
#> 118.3 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 163 24.00 0 66 0 0
#> 116.1 24.00 0 58 0 1
#> 27.1 24.00 0 63 1 0
#> 71 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 74 24.00 0 43 0 1
#> 75.1 24.00 0 21 1 0
#> 53 24.00 0 32 0 1
#> 83 24.00 0 6 0 0
#> 109 24.00 0 48 0 0
#> 151.1 24.00 0 42 0 0
#> 22 24.00 0 52 1 0
#> 143 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 146.1 24.00 0 63 1 0
#> 7 24.00 0 37 1 0
#> 67 24.00 0 25 0 0
#> 98 24.00 0 34 1 0
#> 135 24.00 0 58 1 0
#> 141 24.00 0 44 1 0
#> 146.2 24.00 0 63 1 0
#> 146.3 24.00 0 63 1 0
#> 98.1 24.00 0 34 1 0
#> 28 24.00 0 67 1 0
#> 65 24.00 0 57 1 0
#> 7.1 24.00 0 37 1 0
#> 9 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 144 24.00 0 28 0 1
#> 182 24.00 0 35 0 0
#> 116.2 24.00 0 58 0 1
#> 84 24.00 0 39 0 1
#> 173 24.00 0 19 0 1
#> 94.1 24.00 0 51 0 1
#> 120 24.00 0 68 0 1
#> 148.1 24.00 0 61 1 0
#> 62.2 24.00 0 71 0 0
#> 193 24.00 0 45 0 1
#> 152.1 24.00 0 36 0 1
#> 109.1 24.00 0 48 0 0
#> 11 24.00 0 42 0 1
#> 152.2 24.00 0 36 0 1
#> 196 24.00 0 19 0 0
#> 74.1 24.00 0 43 0 1
#> 33 24.00 0 53 0 0
#> 186 24.00 0 45 1 0
#> 156.2 24.00 0 50 1 0
#> 48 24.00 0 31 1 0
#> 83.1 24.00 0 6 0 0
#> 67.1 24.00 0 25 0 0
#> 135.1 24.00 0 58 1 0
#> 135.2 24.00 0 58 1 0
#> 75.2 24.00 0 21 1 0
#> 71.1 24.00 0 51 0 0
#> 141.2 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.722 NA NA NA
#> 2 age, Cure model 0.0165 NA NA NA
#> 3 grade_ii, Cure model -0.372 NA NA NA
#> 4 grade_iii, Cure model 0.853 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00835 NA NA NA
#> 2 grade_ii, Survival model 0.298 NA NA NA
#> 3 grade_iii, Survival model 0.269 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.72176 0.01654 -0.37190 0.85262
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 251.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.72176478 0.01654259 -0.37190058 0.85261986
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.008352158 0.297604632 0.268869092
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.52830915 0.46342961 0.86458128 0.07078093 0.72320486 0.50119858
#> [7] 0.29217673 0.34290033 0.90623958 0.47320483 0.54596328 0.77076506
#> [13] 0.91785555 0.61105441 0.85237031 0.57868402 0.80245630 0.96811035
#> [19] 0.34290033 0.93501420 0.51929829 0.25277040 0.77076506 0.75749661
#> [25] 0.96811035 0.92932466 0.63463839 0.43328106 0.99474336 0.64241949
#> [31] 0.59510117 0.77076506 0.36667103 0.95158310 0.92360827 0.97885684
#> [37] 0.49191530 0.29217673 0.65776656 0.53724486 0.25277040 0.07078093
#> [43] 0.73020458 0.57868402 0.75749661 0.54596328 0.88855080 0.50119858
#> [49] 0.82147586 0.74399878 0.18849513 0.61895385 0.40089856 0.90037132
#> [55] 0.80883822 0.77076506 0.44367870 0.31828930 0.93501420 0.37857183
#> [61] 0.74399878 0.14228957 0.77076506 0.25277040 0.20923298 0.42255419
#> [67] 0.54596328 0.31828930 0.87063926 0.93501420 0.95712477 0.62681115
#> [73] 0.98945328 0.89447806 0.69471125 0.83402598 0.87668918 0.97885684
#> [79] 0.68005774 0.70909479 0.73713763 0.96263882 0.87668918 0.20923298
#> [85] 0.67262027 0.54596328 0.81516881 0.83402598 0.68741044 0.82776542
#> [91] 0.70193407 0.71618128 0.59510117 0.44367870 0.47320483 0.65012479
#> [97] 0.20923298 0.85848292 0.40089856 0.14228957 0.83402598 0.91206581
#> [103] 0.37857183 0.65776656 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 150 90 123 78 85 68 113 15 107 32 105 39 52
#> 20.33 20.94 13.00 23.88 16.44 20.62 22.86 22.68 11.18 20.90 19.75 15.59 10.42
#> 97 13 58 167 16 15.1 145 128 69 39.1 26 16.1 61
#> 19.14 14.34 19.34 15.55 8.71 22.68 10.07 20.35 23.23 15.59 15.77 8.71 10.12
#> 88 139 127 108 76 39.2 169 101 93 77 190 113.1 134
#> 18.37 21.49 3.53 18.29 19.22 15.59 22.41 9.97 10.33 7.27 20.81 22.86 17.81
#> 158 69.1 78.1 5 58.1 26.1 105.1 154 68.1 180 100 164 179
#> 20.14 23.23 23.88 16.43 19.34 15.77 19.75 12.63 20.62 14.82 16.07 23.60 18.63
#> 66 56 18 39.3 36 63 145.1 194 100.1 86 39.4 69.2 129
#> 22.13 12.21 15.21 15.59 21.19 22.77 10.07 22.40 16.07 23.81 15.59 23.23 23.41
#> 136 105.2 63.1 14 145.2 187 8 25 177 106 96 140 77.1
#> 21.83 19.75 22.77 12.89 10.07 9.92 18.43 6.32 12.53 16.67 14.54 12.68 7.27
#> 45 130 79 183 140.1 129.1 184 105.3 157 96.1 23 133 171
#> 17.42 16.47 16.23 9.24 12.68 23.41 17.77 19.75 15.10 14.54 16.92 14.65 16.57
#> 181 76.1 99 32.1 40 129.2 81 66.1 86.1 96.2 159 194.1 134.1
#> 16.46 19.22 21.19 20.90 18.00 23.41 14.06 22.13 23.81 14.54 10.55 22.40 17.81
#> 31 142 34 131 152 161 156 156.1 172 2 174 160 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 118 142.1 160.1 118.1 62 118.2 102 64 151 162 34.1 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 148 62.1 118.3 75 163 116.1 27.1 71 165 74 75.1 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 109 151.1 22 143 146 119 146.1 7 67 98 135 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146.2 146.3 98.1 28 65 7.1 9 141.1 1 144 182 116.2 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 94.1 120 148.1 62.2 193 152.1 109.1 11 152.2 196 74.1 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 156.2 48 83.1 67.1 135.1 135.2 75.2 71.1 141.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[11]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0121588431 0.2628257062 0.0002958544
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.86179766 0.01503535 0.19155221
#> grade_iii, Cure model
#> 0.62341598
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 4 17.64 1 NA 0 1
#> 114 13.68 1 NA 0 0
#> 164 23.60 1 76 0 1
#> 14 12.89 1 21 0 0
#> 113 22.86 1 34 0 0
#> 133 14.65 1 57 0 0
#> 13 14.34 1 54 0 1
#> 37 12.52 1 57 1 0
#> 76 19.22 1 54 0 1
#> 51 18.23 1 83 0 1
#> 13.1 14.34 1 54 0 1
#> 88 18.37 1 47 0 0
#> 155 13.08 1 26 0 0
#> 130 16.47 1 53 0 1
#> 130.1 16.47 1 53 0 1
#> 136 21.83 1 43 0 1
#> 179 18.63 1 42 0 0
#> 70 7.38 1 30 1 0
#> 100 16.07 1 60 0 0
#> 30 17.43 1 78 0 0
#> 117 17.46 1 26 0 1
#> 139 21.49 1 63 1 0
#> 166 19.98 1 48 0 0
#> 79 16.23 1 54 1 0
#> 155.1 13.08 1 26 0 0
#> 127 3.53 1 62 0 1
#> 158 20.14 1 74 1 0
#> 101 9.97 1 10 0 1
#> 79.1 16.23 1 54 1 0
#> 97 19.14 1 65 0 1
#> 51.1 18.23 1 83 0 1
#> 91 5.33 1 61 0 1
#> 23 16.92 1 61 0 0
#> 86 23.81 1 58 0 1
#> 93 10.33 1 52 0 1
#> 124 9.73 1 NA 1 0
#> 136.1 21.83 1 43 0 1
#> 92 22.92 1 47 0 1
#> 113.1 22.86 1 34 0 0
#> 81 14.06 1 34 0 0
#> 125 15.65 1 67 1 0
#> 13.2 14.34 1 54 0 1
#> 136.2 21.83 1 43 0 1
#> 167 15.55 1 56 1 0
#> 108 18.29 1 39 0 1
#> 60 13.15 1 38 1 0
#> 26 15.77 1 49 0 1
#> 60.1 13.15 1 38 1 0
#> 43 12.10 1 61 0 1
#> 51.2 18.23 1 83 0 1
#> 4.1 17.64 1 NA 0 1
#> 8 18.43 1 32 0 0
#> 100.1 16.07 1 60 0 0
#> 129 23.41 1 53 1 0
#> 157 15.10 1 47 0 0
#> 133.1 14.65 1 57 0 0
#> 168 23.72 1 70 0 0
#> 51.3 18.23 1 83 0 1
#> 192 16.44 1 31 1 0
#> 89 11.44 1 NA 0 0
#> 97.1 19.14 1 65 0 1
#> 57 14.46 1 45 0 1
#> 168.1 23.72 1 70 0 0
#> 81.1 14.06 1 34 0 0
#> 114.1 13.68 1 NA 0 0
#> 101.1 9.97 1 10 0 1
#> 37.1 12.52 1 57 1 0
#> 158.1 20.14 1 74 1 0
#> 154 12.63 1 20 1 0
#> 23.1 16.92 1 61 0 0
#> 57.1 14.46 1 45 0 1
#> 190 20.81 1 42 1 0
#> 164.1 23.60 1 76 0 1
#> 58 19.34 1 39 0 0
#> 8.1 18.43 1 32 0 0
#> 32 20.90 1 37 1 0
#> 166.1 19.98 1 48 0 0
#> 97.2 19.14 1 65 0 1
#> 129.1 23.41 1 53 1 0
#> 164.2 23.60 1 76 0 1
#> 136.3 21.83 1 43 0 1
#> 189 10.51 1 NA 1 0
#> 97.3 19.14 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 41 18.02 1 40 1 0
#> 145 10.07 1 65 1 0
#> 13.3 14.34 1 54 0 1
#> 63 22.77 1 31 1 0
#> 41.1 18.02 1 40 1 0
#> 190.1 20.81 1 42 1 0
#> 10 10.53 1 34 0 0
#> 187 9.92 1 39 1 0
#> 199 19.81 1 NA 0 1
#> 127.1 3.53 1 62 0 1
#> 93.1 10.33 1 52 0 1
#> 29 15.45 1 68 1 0
#> 125.1 15.65 1 67 1 0
#> 150 20.33 1 48 0 0
#> 88.1 18.37 1 47 0 0
#> 4.2 17.64 1 NA 0 1
#> 145.1 10.07 1 65 1 0
#> 159 10.55 1 50 0 1
#> 81.2 14.06 1 34 0 0
#> 49 12.19 1 48 1 0
#> 69 23.23 1 25 0 1
#> 68 20.62 1 44 0 0
#> 105 19.75 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 69.1 23.23 1 25 0 1
#> 96 14.54 1 33 0 1
#> 176 24.00 0 43 0 1
#> 182 24.00 0 35 0 0
#> 54 24.00 0 53 1 0
#> 1 24.00 0 23 1 0
#> 165 24.00 0 47 0 0
#> 71 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 191 24.00 0 60 0 1
#> 131 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 72 24.00 0 40 0 1
#> 103 24.00 0 56 1 0
#> 143 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 87 24.00 0 27 0 0
#> 152 24.00 0 36 0 1
#> 144 24.00 0 28 0 1
#> 65 24.00 0 57 1 0
#> 112 24.00 0 61 0 0
#> 162 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 198 24.00 0 66 0 1
#> 121 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 67 24.00 0 25 0 0
#> 160 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 191.1 24.00 0 60 0 1
#> 162.1 24.00 0 51 0 0
#> 191.2 24.00 0 60 0 1
#> 87.1 24.00 0 27 0 0
#> 11 24.00 0 42 0 1
#> 132 24.00 0 55 0 0
#> 185 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 147 24.00 0 76 1 0
#> 84.1 24.00 0 39 0 1
#> 163 24.00 0 66 0 0
#> 87.2 24.00 0 27 0 0
#> 142 24.00 0 53 0 0
#> 48 24.00 0 31 1 0
#> 176.1 24.00 0 43 0 1
#> 143.1 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 112.1 24.00 0 61 0 0
#> 143.2 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 165.1 24.00 0 47 0 0
#> 74 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 176.2 24.00 0 43 0 1
#> 193 24.00 0 45 0 1
#> 82 24.00 0 34 0 0
#> 9.1 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 71.1 24.00 0 51 0 0
#> 131.1 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 71.2 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 178 24.00 0 52 1 0
#> 172.1 24.00 0 41 0 0
#> 161 24.00 0 45 0 0
#> 152.1 24.00 0 36 0 1
#> 35 24.00 0 51 0 0
#> 84.2 24.00 0 39 0 1
#> 196 24.00 0 19 0 0
#> 200 24.00 0 64 0 0
#> 3 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 31.1 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 22 24.00 0 52 1 0
#> 191.3 24.00 0 60 0 1
#> 34 24.00 0 36 0 0
#> 186 24.00 0 45 1 0
#> 12 24.00 0 63 0 0
#> 28 24.00 0 67 1 0
#> 65.1 24.00 0 57 1 0
#> 185.1 24.00 0 44 1 0
#> 178.1 24.00 0 52 1 0
#> 2 24.00 0 9 0 0
#> 95.1 24.00 0 68 0 1
#> 135 24.00 0 58 1 0
#> 54.1 24.00 0 53 1 0
#> 28.1 24.00 0 67 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.862 NA NA NA
#> 2 age, Cure model 0.0150 NA NA NA
#> 3 grade_ii, Cure model 0.192 NA NA NA
#> 4 grade_iii, Cure model 0.623 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0122 NA NA NA
#> 2 grade_ii, Survival model 0.263 NA NA NA
#> 3 grade_iii, Survival model 0.000296 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86180 0.01504 0.19155 0.62342
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 261.1
#> Residual Deviance: 254.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86179766 0.01503535 0.19155221 0.62341598
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0121588431 0.2628257062 0.0002958544
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 2.804439e-03 6.926771e-01 2.617566e-02 4.760248e-01 5.406297e-01
#> [6] 7.364552e-01 1.292596e-01 2.166454e-01 5.406297e-01 1.907556e-01
#> [11] 6.640722e-01 3.140551e-01 3.140551e-01 3.895978e-02 1.661973e-01
#> [16] 9.356220e-01 3.799691e-01 2.829803e-01 2.729742e-01 5.695713e-02
#> [21] 1.024798e-01 3.465610e-01 6.640722e-01 9.675916e-01 9.024361e-02
#> [26] 8.883340e-01 3.465610e-01 1.364517e-01 2.166454e-01 9.515365e-01
#> [31] 2.932079e-01 8.406802e-05 8.262483e-01 3.895978e-02 2.212350e-02
#> [36] 2.617566e-02 5.941914e-01 4.148829e-01 5.406297e-01 3.895978e-02
#> [41] 4.388246e-01 2.078006e-01 6.357976e-01 4.030288e-01 6.357976e-01
#> [46] 7.807240e-01 2.166454e-01 1.743492e-01 3.799691e-01 9.140695e-03
#> [51] 4.634789e-01 4.760248e-01 6.360677e-04 2.166454e-01 3.355810e-01
#> [56] 1.364517e-01 5.144339e-01 6.360677e-04 5.941914e-01 8.883340e-01
#> [61] 7.364552e-01 9.024361e-02 7.218298e-01 2.932079e-01 5.144339e-01
#> [66] 6.773834e-02 2.804439e-03 1.222552e-01 1.743492e-01 6.230784e-02
#> [71] 1.024798e-01 1.364517e-01 9.140695e-03 2.804439e-03 3.895978e-02
#> [76] 1.364517e-01 7.071986e-01 2.535185e-01 8.570607e-01 5.406297e-01
#> [81] 3.446659e-02 2.535185e-01 6.773834e-02 8.109653e-01 9.197337e-01
#> [86] 9.675916e-01 8.262483e-01 4.510791e-01 4.148829e-01 8.429750e-02
#> [91] 1.907556e-01 8.570607e-01 7.957793e-01 5.941914e-01 7.658193e-01
#> [96] 1.525565e-02 7.853130e-02 1.153992e-01 3.686212e-01 1.525565e-02
#> [101] 5.014472e-01 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 164 14 113 133 13 37 76 51 13.1 88 155 130 130.1
#> 23.60 12.89 22.86 14.65 14.34 12.52 19.22 18.23 14.34 18.37 13.08 16.47 16.47
#> 136 179 70 100 30 117 139 166 79 155.1 127 158 101
#> 21.83 18.63 7.38 16.07 17.43 17.46 21.49 19.98 16.23 13.08 3.53 20.14 9.97
#> 79.1 97 51.1 91 23 86 93 136.1 92 113.1 81 125 13.2
#> 16.23 19.14 18.23 5.33 16.92 23.81 10.33 21.83 22.92 22.86 14.06 15.65 14.34
#> 136.2 167 108 60 26 60.1 43 51.2 8 100.1 129 157 133.1
#> 21.83 15.55 18.29 13.15 15.77 13.15 12.10 18.23 18.43 16.07 23.41 15.10 14.65
#> 168 51.3 192 97.1 57 168.1 81.1 101.1 37.1 158.1 154 23.1 57.1
#> 23.72 18.23 16.44 19.14 14.46 23.72 14.06 9.97 12.52 20.14 12.63 16.92 14.46
#> 190 164.1 58 8.1 32 166.1 97.2 129.1 164.2 136.3 97.3 140 41
#> 20.81 23.60 19.34 18.43 20.90 19.98 19.14 23.41 23.60 21.83 19.14 12.68 18.02
#> 145 13.3 63 41.1 190.1 10 187 127.1 93.1 29 125.1 150 88.1
#> 10.07 14.34 22.77 18.02 20.81 10.53 9.92 3.53 10.33 15.45 15.65 20.33 18.37
#> 145.1 159 81.2 49 69 68 105 188 69.1 96 176 182 54
#> 10.07 10.55 14.06 12.19 23.23 20.62 19.75 16.16 23.23 14.54 24.00 24.00 24.00
#> 1 165 71 137 191 131 141 84 72 103 143 83 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 144 65 112 162 94 198 121 53 67 160 156 191.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 191.2 87.1 11 132 185 31 147 84.1 163 87.2 142 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 143.1 9 80 112.1 143.2 104 165.1 74 172 176.2 193 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 119 71.1 131.1 20 71.2 95 178 172.1 161 152.1 35 84.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 200 3 120 31.1 109 22 191.3 34 186 12 28 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 178.1 2 95.1 135 54.1 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[12]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002786874 0.639934621 0.151145276
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.353760661 0.008725421 -0.028755588
#> grade_iii, Cure model
#> 0.408264251
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 157 15.10 1 47 0 0
#> 170 19.54 1 43 0 1
#> 189 10.51 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 145 10.07 1 65 1 0
#> 125 15.65 1 67 1 0
#> 190 20.81 1 42 1 0
#> 133.1 14.65 1 57 0 0
#> 108 18.29 1 39 0 1
#> 117 17.46 1 26 0 1
#> 68 20.62 1 44 0 0
#> 189.1 10.51 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 43 12.10 1 61 0 1
#> 117.1 17.46 1 26 0 1
#> 134 17.81 1 47 1 0
#> 40 18.00 1 28 1 0
#> 113 22.86 1 34 0 0
#> 91 5.33 1 61 0 1
#> 59 10.16 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 183 9.24 1 67 1 0
#> 169 22.41 1 46 0 0
#> 90 20.94 1 50 0 1
#> 4 17.64 1 NA 0 1
#> 40.1 18.00 1 28 1 0
#> 106.1 16.67 1 49 1 0
#> 128 20.35 1 35 0 1
#> 76 19.22 1 54 0 1
#> 194 22.40 1 38 0 1
#> 58 19.34 1 39 0 0
#> 108.1 18.29 1 39 0 1
#> 86 23.81 1 58 0 1
#> 100 16.07 1 60 0 0
#> 139 21.49 1 63 1 0
#> 76.1 19.22 1 54 0 1
#> 127 3.53 1 62 0 1
#> 139.1 21.49 1 63 1 0
#> 106.2 16.67 1 49 1 0
#> 92 22.92 1 47 0 1
#> 197 21.60 1 69 1 0
#> 63 22.77 1 31 1 0
#> 100.1 16.07 1 60 0 0
#> 106.3 16.67 1 49 1 0
#> 58.1 19.34 1 39 0 0
#> 155 13.08 1 26 0 0
#> 150 20.33 1 48 0 0
#> 113.1 22.86 1 34 0 0
#> 168 23.72 1 70 0 0
#> 79 16.23 1 54 1 0
#> 45 17.42 1 54 0 1
#> 59.1 10.16 1 NA 1 0
#> 90.1 20.94 1 50 0 1
#> 99 21.19 1 38 0 1
#> 66 22.13 1 53 0 0
#> 39 15.59 1 37 0 1
#> 70 7.38 1 30 1 0
#> 179 18.63 1 42 0 0
#> 177 12.53 1 75 0 0
#> 86.1 23.81 1 58 0 1
#> 107 11.18 1 54 1 0
#> 24 23.89 1 38 0 0
#> 10 10.53 1 34 0 0
#> 6 15.64 1 39 0 0
#> 66.1 22.13 1 53 0 0
#> 133.2 14.65 1 57 0 0
#> 13 14.34 1 54 0 1
#> 187 9.92 1 39 1 0
#> 79.1 16.23 1 54 1 0
#> 136 21.83 1 43 0 1
#> 79.2 16.23 1 54 1 0
#> 180 14.82 1 37 0 0
#> 43.1 12.10 1 61 0 1
#> 169.1 22.41 1 46 0 0
#> 5 16.43 1 51 0 1
#> 164 23.60 1 76 0 1
#> 15 22.68 1 48 0 0
#> 59.2 10.16 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 93 10.33 1 52 0 1
#> 180.1 14.82 1 37 0 0
#> 8 18.43 1 32 0 0
#> 108.2 18.29 1 39 0 1
#> 49 12.19 1 48 1 0
#> 5.1 16.43 1 51 0 1
#> 136.1 21.83 1 43 0 1
#> 150.1 20.33 1 48 0 0
#> 189.2 10.51 1 NA 1 0
#> 180.2 14.82 1 37 0 0
#> 134.1 17.81 1 47 1 0
#> 183.1 9.24 1 67 1 0
#> 155.1 13.08 1 26 0 0
#> 32 20.90 1 37 1 0
#> 155.2 13.08 1 26 0 0
#> 15.1 22.68 1 48 0 0
#> 30 17.43 1 78 0 0
#> 136.2 21.83 1 43 0 1
#> 123 13.00 1 44 1 0
#> 60 13.15 1 38 1 0
#> 166 19.98 1 48 0 0
#> 127.1 3.53 1 62 0 1
#> 199 19.81 1 NA 0 1
#> 181 16.46 1 45 0 1
#> 41 18.02 1 40 1 0
#> 36 21.19 1 48 0 1
#> 4.1 17.64 1 NA 0 1
#> 134.2 17.81 1 47 1 0
#> 99.1 21.19 1 38 0 1
#> 168.1 23.72 1 70 0 0
#> 29 15.45 1 68 1 0
#> 78 23.88 1 43 0 0
#> 99.2 21.19 1 38 0 1
#> 53 24.00 0 32 0 1
#> 141 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 73 24.00 0 NA 0 1
#> 104 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 35 24.00 0 51 0 0
#> 198 24.00 0 66 0 1
#> 1 24.00 0 23 1 0
#> 38 24.00 0 31 1 0
#> 73.1 24.00 0 NA 0 1
#> 64 24.00 0 43 0 0
#> 172 24.00 0 41 0 0
#> 22 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 132 24.00 0 55 0 0
#> 118 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 144 24.00 0 28 0 1
#> 165 24.00 0 47 0 0
#> 46 24.00 0 71 0 0
#> 160 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 172.1 24.00 0 41 0 0
#> 17 24.00 0 38 0 1
#> 94 24.00 0 51 0 1
#> 132.1 24.00 0 55 0 0
#> 161 24.00 0 45 0 0
#> 98 24.00 0 34 1 0
#> 53.1 24.00 0 32 0 1
#> 21 24.00 0 47 0 0
#> 151 24.00 0 42 0 0
#> 193 24.00 0 45 0 1
#> 162 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 141.1 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 34 24.00 0 36 0 0
#> 144.1 24.00 0 28 0 1
#> 54 24.00 0 53 1 0
#> 83 24.00 0 6 0 0
#> 38.1 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 33.1 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 53.2 24.00 0 32 0 1
#> 118.1 24.00 0 44 1 0
#> 116.1 24.00 0 58 0 1
#> 198.1 24.00 0 66 0 1
#> 163.1 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 53.3 24.00 0 32 0 1
#> 48 24.00 0 31 1 0
#> 146.1 24.00 0 63 1 0
#> 109 24.00 0 48 0 0
#> 54.1 24.00 0 53 1 0
#> 22.1 24.00 0 52 1 0
#> 142 24.00 0 53 0 0
#> 142.1 24.00 0 53 0 0
#> 116.2 24.00 0 58 0 1
#> 186.1 24.00 0 45 1 0
#> 148.1 24.00 0 61 1 0
#> 53.4 24.00 0 32 0 1
#> 1.1 24.00 0 23 1 0
#> 71 24.00 0 51 0 0
#> 95.1 24.00 0 68 0 1
#> 35.1 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 65.1 24.00 0 57 1 0
#> 47 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 182 24.00 0 35 0 0
#> 95.2 24.00 0 68 0 1
#> 83.1 24.00 0 6 0 0
#> 38.2 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 200 24.00 0 64 0 0
#> 34.1 24.00 0 36 0 0
#> 62.1 24.00 0 71 0 0
#> 172.2 24.00 0 41 0 0
#> 11 24.00 0 42 0 1
#> 182.1 24.00 0 35 0 0
#> 132.2 24.00 0 55 0 0
#> 38.3 24.00 0 31 1 0
#> 53.5 24.00 0 32 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.354 NA NA NA
#> 2 age, Cure model 0.00873 NA NA NA
#> 3 grade_ii, Cure model -0.0288 NA NA NA
#> 4 grade_iii, Cure model 0.408 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00279 NA NA NA
#> 2 grade_ii, Survival model 0.640 NA NA NA
#> 3 grade_iii, Survival model 0.151 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.353761 0.008725 -0.028756 0.408264
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 257 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.353760661 0.008725421 -0.028755588 0.408264251
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002786874 0.639934621 0.151145276
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.758334406 0.420639251 0.793200639 0.932492220 0.723129853 0.360167144
#> [7] 0.793200639 0.491680731 0.579083418 0.370236173 0.889276569 0.579083418
#> [13] 0.551198323 0.531791063 0.112173111 0.974863790 0.616676139 0.949630555
#> [19] 0.168009063 0.329245811 0.531791063 0.616676139 0.380336918 0.451003053
#> [25] 0.190266369 0.430808133 0.491680731 0.030744942 0.705494421 0.268323904
#> [31] 0.451003053 0.983264416 0.268323904 0.616676139 0.100387696 0.257149088
#> [37] 0.134929341 0.705494421 0.616676139 0.430808133 0.837029768 0.390422929
#> [43] 0.112173111 0.052291555 0.679307467 0.607226362 0.329245811 0.289203174
#> [49] 0.201709309 0.740761126 0.966464515 0.471197533 0.871847884 0.030744942
#> [55] 0.906569881 0.005779312 0.915205913 0.731940021 0.201709309 0.793200639
#> [61] 0.819423884 0.941088738 0.679307467 0.224290071 0.679307467 0.767104180
#> [67] 0.889276569 0.168009063 0.661294160 0.075674108 0.146104597 0.088575675
#> [73] 0.923849319 0.767104180 0.481429834 0.491680731 0.880590637 0.661294160
#> [79] 0.224290071 0.390422929 0.767104180 0.551198323 0.949630555 0.837029768
#> [85] 0.349901006 0.837029768 0.146104597 0.597776492 0.224290071 0.863121637
#> [91] 0.828259842 0.410462556 0.983264416 0.652223085 0.521717531 0.289203174
#> [97] 0.551198323 0.289203174 0.052291555 0.749577067 0.017566555 0.289203174
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 157 170 133 145 125 190 133.1 108 117 68 43 117.1 134
#> 15.10 19.54 14.65 10.07 15.65 20.81 14.65 18.29 17.46 20.62 12.10 17.46 17.81
#> 40 113 91 106 183 169 90 40.1 106.1 128 76 194 58
#> 18.00 22.86 5.33 16.67 9.24 22.41 20.94 18.00 16.67 20.35 19.22 22.40 19.34
#> 108.1 86 100 139 76.1 127 139.1 106.2 92 197 63 100.1 106.3
#> 18.29 23.81 16.07 21.49 19.22 3.53 21.49 16.67 22.92 21.60 22.77 16.07 16.67
#> 58.1 155 150 113.1 168 79 45 90.1 99 66 39 70 179
#> 19.34 13.08 20.33 22.86 23.72 16.23 17.42 20.94 21.19 22.13 15.59 7.38 18.63
#> 177 86.1 107 24 10 6 66.1 133.2 13 187 79.1 136 79.2
#> 12.53 23.81 11.18 23.89 10.53 15.64 22.13 14.65 14.34 9.92 16.23 21.83 16.23
#> 180 43.1 169.1 5 164 15 129 93 180.1 8 108.2 49 5.1
#> 14.82 12.10 22.41 16.43 23.60 22.68 23.41 10.33 14.82 18.43 18.29 12.19 16.43
#> 136.1 150.1 180.2 134.1 183.1 155.1 32 155.2 15.1 30 136.2 123 60
#> 21.83 20.33 14.82 17.81 9.24 13.08 20.90 13.08 22.68 17.43 21.83 13.00 13.15
#> 166 127.1 181 41 36 134.2 99.1 168.1 29 78 99.2 53 141
#> 19.98 3.53 16.46 18.02 21.19 17.81 21.19 23.72 15.45 23.88 21.19 24.00 24.00
#> 116 104 65 186 35 198 1 38 64 172 22 33 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 118 163 62 144 165 46 160 146 172.1 17 94 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 98 53.1 21 151 193 162 27 141.1 135 34 144.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 38.1 44 33.1 178 53.2 118.1 116.1 198.1 163.1 95 53.3 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146.1 109 54.1 22.1 142 142.1 116.2 186.1 148.1 53.4 1.1 71 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.1 87 65.1 47 7 182 95.2 83.1 38.2 72 200 34.1 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.2 11 182.1 132.2 38.3 53.5
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[13]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02021353 1.04554466 0.52526292
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.89332230 0.01444614 0.19457562
#> grade_iii, Cure model
#> 0.83593362
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 123 13.00 1 44 1 0
#> 89 11.44 1 NA 0 0
#> 91 5.33 1 61 0 1
#> 57 14.46 1 45 0 1
#> 49 12.19 1 48 1 0
#> 42 12.43 1 49 0 1
#> 129 23.41 1 53 1 0
#> 93 10.33 1 52 0 1
#> 197 21.60 1 69 1 0
#> 89.1 11.44 1 NA 0 0
#> 24 23.89 1 38 0 0
#> 25 6.32 1 34 1 0
#> 81 14.06 1 34 0 0
#> 177 12.53 1 75 0 0
#> 187 9.92 1 39 1 0
#> 107 11.18 1 54 1 0
#> 90 20.94 1 50 0 1
#> 197.1 21.60 1 69 1 0
#> 4 17.64 1 NA 0 1
#> 14 12.89 1 21 0 0
#> 154 12.63 1 20 1 0
#> 25.1 6.32 1 34 1 0
#> 197.2 21.60 1 69 1 0
#> 37 12.52 1 57 1 0
#> 92 22.92 1 47 0 1
#> 58 19.34 1 39 0 0
#> 153 21.33 1 55 1 0
#> 164 23.60 1 76 0 1
#> 145 10.07 1 65 1 0
#> 42.1 12.43 1 49 0 1
#> 97 19.14 1 65 0 1
#> 79 16.23 1 54 1 0
#> 145.1 10.07 1 65 1 0
#> 85 16.44 1 36 0 0
#> 123.1 13.00 1 44 1 0
#> 183 9.24 1 67 1 0
#> 51 18.23 1 83 0 1
#> 125 15.65 1 67 1 0
#> 195 11.76 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 97.1 19.14 1 65 0 1
#> 10 10.53 1 34 0 0
#> 105 19.75 1 60 0 0
#> 6 15.64 1 39 0 0
#> 114 13.68 1 NA 0 0
#> 194.1 22.40 1 38 0 1
#> 184 17.77 1 38 0 0
#> 49.1 12.19 1 48 1 0
#> 129.1 23.41 1 53 1 0
#> 114.1 13.68 1 NA 0 0
#> 76 19.22 1 54 0 1
#> 52 10.42 1 52 0 1
#> 89.2 11.44 1 NA 0 0
#> 108 18.29 1 39 0 1
#> 77 7.27 1 67 0 1
#> 195.1 11.76 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 100 16.07 1 60 0 0
#> 125.1 15.65 1 67 1 0
#> 145.2 10.07 1 65 1 0
#> 99 21.19 1 38 0 1
#> 194.2 22.40 1 38 0 1
#> 199 19.81 1 NA 0 1
#> 70 7.38 1 30 1 0
#> 14.1 12.89 1 21 0 0
#> 179 18.63 1 42 0 0
#> 127 3.53 1 62 0 1
#> 25.2 6.32 1 34 1 0
#> 23 16.92 1 61 0 0
#> 195.2 11.76 1 NA 1 0
#> 130.1 16.47 1 53 0 1
#> 139 21.49 1 63 1 0
#> 86 23.81 1 58 0 1
#> 24.1 23.89 1 38 0 0
#> 68 20.62 1 44 0 0
#> 45 17.42 1 54 0 1
#> 39 15.59 1 37 0 1
#> 51.1 18.23 1 83 0 1
#> 175 21.91 1 43 0 0
#> 26 15.77 1 49 0 1
#> 91.1 5.33 1 61 0 1
#> 107.1 11.18 1 54 1 0
#> 181 16.46 1 45 0 1
#> 66 22.13 1 53 0 0
#> 199.1 19.81 1 NA 0 1
#> 8 18.43 1 32 0 0
#> 150 20.33 1 48 0 0
#> 168 23.72 1 70 0 0
#> 42.2 12.43 1 49 0 1
#> 168.1 23.72 1 70 0 0
#> 5 16.43 1 51 0 1
#> 101 9.97 1 10 0 1
#> 128 20.35 1 35 0 1
#> 13 14.34 1 54 0 1
#> 169 22.41 1 46 0 0
#> 169.1 22.41 1 46 0 0
#> 85.1 16.44 1 36 0 0
#> 136 21.83 1 43 0 1
#> 91.2 5.33 1 61 0 1
#> 68.1 20.62 1 44 0 0
#> 14.2 12.89 1 21 0 0
#> 59 10.16 1 NA 1 0
#> 25.3 6.32 1 34 1 0
#> 85.2 16.44 1 36 0 0
#> 179.1 18.63 1 42 0 0
#> 39.1 15.59 1 37 0 1
#> 50 10.02 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 123.2 13.00 1 44 1 0
#> 76.1 19.22 1 54 0 1
#> 35 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 104 24.00 0 50 1 0
#> 9 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 95 24.00 0 68 0 1
#> 162 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 174 24.00 0 49 1 0
#> 94 24.00 0 51 0 1
#> 141 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 12 24.00 0 63 0 0
#> 112 24.00 0 61 0 0
#> 138 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 148 24.00 0 61 1 0
#> 121 24.00 0 57 1 0
#> 151 24.00 0 42 0 0
#> 121.1 24.00 0 57 1 0
#> 120 24.00 0 68 0 1
#> 173.1 24.00 0 19 0 1
#> 161 24.00 0 45 0 0
#> 152 24.00 0 36 0 1
#> 53 24.00 0 32 0 1
#> 104.1 24.00 0 50 1 0
#> 126 24.00 0 48 0 0
#> 48 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 119 24.00 0 17 0 0
#> 146 24.00 0 63 1 0
#> 3 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 135 24.00 0 58 1 0
#> 33 24.00 0 53 0 0
#> 176 24.00 0 43 0 1
#> 200 24.00 0 64 0 0
#> 7 24.00 0 37 1 0
#> 67 24.00 0 25 0 0
#> 121.2 24.00 0 57 1 0
#> 174.1 24.00 0 49 1 0
#> 141.1 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 122 24.00 0 66 0 0
#> 174.2 24.00 0 49 1 0
#> 21 24.00 0 47 0 0
#> 198 24.00 0 66 0 1
#> 200.1 24.00 0 64 0 0
#> 62.1 24.00 0 71 0 0
#> 141.2 24.00 0 44 1 0
#> 9.1 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 122.1 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 102 24.00 0 49 0 0
#> 82.1 24.00 0 34 0 0
#> 48.1 24.00 0 31 1 0
#> 112.1 24.00 0 61 0 0
#> 20 24.00 0 46 1 0
#> 143 24.00 0 51 0 0
#> 147 24.00 0 76 1 0
#> 98 24.00 0 34 1 0
#> 3.1 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 17 24.00 0 38 0 1
#> 112.2 24.00 0 61 0 0
#> 83.1 24.00 0 6 0 0
#> 53.1 24.00 0 32 0 1
#> 172 24.00 0 41 0 0
#> 102.1 24.00 0 49 0 0
#> 94.1 24.00 0 51 0 1
#> 193.1 24.00 0 45 0 1
#> 17.1 24.00 0 38 0 1
#> 62.2 24.00 0 71 0 0
#> 35.1 24.00 0 51 0 0
#> 146.1 24.00 0 63 1 0
#> 9.2 24.00 0 31 1 0
#> 82.2 24.00 0 34 0 0
#> 186 24.00 0 45 1 0
#> 119.1 24.00 0 17 0 0
#> 156 24.00 0 50 1 0
#> 131 24.00 0 66 0 0
#> 74.1 24.00 0 43 0 1
#> 67.1 24.00 0 25 0 0
#> 151.1 24.00 0 42 0 0
#> 2 24.00 0 9 0 0
#> 95.1 24.00 0 68 0 1
#> 47 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.893 NA NA NA
#> 2 age, Cure model 0.0144 NA NA NA
#> 3 grade_ii, Cure model 0.195 NA NA NA
#> 4 grade_iii, Cure model 0.836 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0202 NA NA NA
#> 2 grade_ii, Survival model 1.05 NA NA NA
#> 3 grade_iii, Survival model 0.525 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.89332 0.01445 0.19458 0.83593
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 257.3
#> Residual Deviance: 249.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.89332230 0.01444614 0.19457562 0.83593362
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02021353 1.04554466 0.52526292
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0304844840 0.5083727713 0.9425281804 0.4535283919 0.6716610743
#> [6] 0.6299700245 0.0092450954 0.7564234123 0.0601729425 0.0001239809
#> [11] 0.8870865629 0.4807302055 0.6022697741 0.8288910420 0.6996594898
#> [16] 0.0962194959 0.0601729425 0.5480167435 0.5886790361 0.8870865629
#> [21] 0.0601729425 0.6161041485 0.0148005033 0.1387804030 0.0835165515
#> [26] 0.0059865338 0.7709508892 0.6299700245 0.1629699178 0.3505481882
#> [31] 0.7709508892 0.3031166740 0.5083727713 0.8434235440 0.2174002358
#> [36] 0.3883065288 0.4946132139 0.1629699178 0.7277084965 0.1310619944
#> [41] 0.4139131496 0.0304844840 0.2373736359 0.6716610743 0.0092450954
#> [46] 0.1467403107 0.7420091490 0.2077919708 0.8724865206 0.2694222365
#> [51] 0.3628798141 0.3883065288 0.7709508892 0.0898195335 0.0304844840
#> [56] 0.8580228739 0.5480167435 0.1801326038 0.9853894374 0.8870865629
#> [61] 0.2584615256 0.2694222365 0.0772441020 0.0010704400 0.0001239809
#> [66] 0.1027875615 0.2478205893 0.4271477031 0.2174002358 0.0487804712
#> [71] 0.3755131051 0.9425281804 0.6996594898 0.2916436033 0.0435225728
#> [76] 0.1982854437 0.1236503125 0.0021320745 0.6299700245 0.0021320745
#> [81] 0.3382360712 0.8142834257 0.1165046660 0.4670436705 0.0219299953
#> [86] 0.0219299953 0.3031166740 0.0543897289 0.9425281804 0.1027875615
#> [91] 0.5480167435 0.8870865629 0.3031166740 0.1801326038 0.4271477031
#> [96] 0.0181482142 0.5083727713 0.1467403107 0.0000000000 0.0000000000
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000
#>
#> $Time
#> 194 123 91 57 49 42 129 93 197 24 25 81 177
#> 22.40 13.00 5.33 14.46 12.19 12.43 23.41 10.33 21.60 23.89 6.32 14.06 12.53
#> 187 107 90 197.1 14 154 25.1 197.2 37 92 58 153 164
#> 9.92 11.18 20.94 21.60 12.89 12.63 6.32 21.60 12.52 22.92 19.34 21.33 23.60
#> 145 42.1 97 79 145.1 85 123.1 183 51 125 60 97.1 10
#> 10.07 12.43 19.14 16.23 10.07 16.44 13.00 9.24 18.23 15.65 13.15 19.14 10.53
#> 105 6 194.1 184 49.1 129.1 76 52 108 77 130 100 125.1
#> 19.75 15.64 22.40 17.77 12.19 23.41 19.22 10.42 18.29 7.27 16.47 16.07 15.65
#> 145.2 99 194.2 70 14.1 179 127 25.2 23 130.1 139 86 24.1
#> 10.07 21.19 22.40 7.38 12.89 18.63 3.53 6.32 16.92 16.47 21.49 23.81 23.89
#> 68 45 39 51.1 175 26 91.1 107.1 181 66 8 150 168
#> 20.62 17.42 15.59 18.23 21.91 15.77 5.33 11.18 16.46 22.13 18.43 20.33 23.72
#> 42.2 168.1 5 101 128 13 169 169.1 85.1 136 91.2 68.1 14.2
#> 12.43 23.72 16.43 9.97 20.35 14.34 22.41 22.41 16.44 21.83 5.33 20.62 12.89
#> 25.3 85.2 179.1 39.1 15 123.2 76.1 35 193 104 9 83 95
#> 6.32 16.44 18.63 15.59 22.68 13.00 19.22 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 82 174 94 141 31 12 112 138 173 148 121 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.1 120 173.1 161 152 53 104.1 126 48 163 119 146 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 135 33 176 200 7 67 121.2 174.1 141.1 182 122 174.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 198 200.1 62.1 141.2 9.1 74 122.1 165 102 82.1 48.1 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 143 147 98 3.1 75 17 112.2 83.1 53.1 172 102.1 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 17.1 62.2 35.1 146.1 9.2 82.2 186 119.1 156 131 74.1 67.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 2 95.1 47
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[14]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002156184 0.756444498 0.252567593
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.19872889 0.00442292 -0.10302469
#> grade_iii, Cure model
#> 0.79922017
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 113 22.86 1 34 0 0
#> 89 11.44 1 NA 0 0
#> 92 22.92 1 47 0 1
#> 179 18.63 1 42 0 0
#> 39 15.59 1 37 0 1
#> 18 15.21 1 49 1 0
#> 26 15.77 1 49 0 1
#> 66 22.13 1 53 0 0
#> 179.1 18.63 1 42 0 0
#> 81 14.06 1 34 0 0
#> 157 15.10 1 47 0 0
#> 59 10.16 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 32 20.90 1 37 1 0
#> 51 18.23 1 83 0 1
#> 14 12.89 1 21 0 0
#> 189 10.51 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 149 8.37 1 33 1 0
#> 127 3.53 1 62 0 1
#> 107 11.18 1 54 1 0
#> 6 15.64 1 39 0 0
#> 85 16.44 1 36 0 0
#> 128 20.35 1 35 0 1
#> 159 10.55 1 50 0 1
#> 181 16.46 1 45 0 1
#> 164 23.60 1 76 0 1
#> 10 10.53 1 34 0 0
#> 145 10.07 1 65 1 0
#> 175 21.91 1 43 0 0
#> 139 21.49 1 63 1 0
#> 78 23.88 1 43 0 0
#> 139.1 21.49 1 63 1 0
#> 113.1 22.86 1 34 0 0
#> 69 23.23 1 25 0 1
#> 6.1 15.64 1 39 0 0
#> 18.1 15.21 1 49 1 0
#> 106 16.67 1 49 1 0
#> 6.2 15.64 1 39 0 0
#> 192 16.44 1 31 1 0
#> 150 20.33 1 48 0 0
#> 77 7.27 1 67 0 1
#> 68 20.62 1 44 0 0
#> 78.1 23.88 1 43 0 0
#> 56 12.21 1 60 0 0
#> 58 19.34 1 39 0 0
#> 130 16.47 1 53 0 1
#> 114 13.68 1 NA 0 0
#> 86 23.81 1 58 0 1
#> 39.1 15.59 1 37 0 1
#> 189.1 10.51 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 58.1 19.34 1 39 0 0
#> 25 6.32 1 34 1 0
#> 86.1 23.81 1 58 0 1
#> 42 12.43 1 49 0 1
#> 106.1 16.67 1 49 1 0
#> 123 13.00 1 44 1 0
#> 15 22.68 1 48 0 0
#> 123.1 13.00 1 44 1 0
#> 140.1 12.68 1 59 1 0
#> 69.1 23.23 1 25 0 1
#> 4 17.64 1 NA 0 1
#> 37 12.52 1 57 1 0
#> 153 21.33 1 55 1 0
#> 170 19.54 1 43 0 1
#> 190 20.81 1 42 1 0
#> 124 9.73 1 NA 1 0
#> 90.1 20.94 1 50 0 1
#> 59.1 10.16 1 NA 1 0
#> 56.1 12.21 1 60 0 0
#> 111.1 17.45 1 47 0 1
#> 16 8.71 1 71 0 1
#> 106.2 16.67 1 49 1 0
#> 85.1 16.44 1 36 0 0
#> 66.1 22.13 1 53 0 0
#> 14.1 12.89 1 21 0 0
#> 117 17.46 1 26 0 1
#> 157.1 15.10 1 47 0 0
#> 110 17.56 1 65 0 1
#> 88 18.37 1 47 0 0
#> 41 18.02 1 40 1 0
#> 139.2 21.49 1 63 1 0
#> 97 19.14 1 65 0 1
#> 37.1 12.52 1 57 1 0
#> 50 10.02 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 124.1 9.73 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 91 5.33 1 61 0 1
#> 93 10.33 1 52 0 1
#> 107.1 11.18 1 54 1 0
#> 99 21.19 1 38 0 1
#> 58.2 19.34 1 39 0 0
#> 45 17.42 1 54 0 1
#> 179.2 18.63 1 42 0 0
#> 30 17.43 1 78 0 0
#> 45.1 17.42 1 54 0 1
#> 40 18.00 1 28 1 0
#> 167 15.55 1 56 1 0
#> 189.2 10.51 1 NA 1 0
#> 197 21.60 1 69 1 0
#> 167.1 15.55 1 56 1 0
#> 96 14.54 1 33 0 1
#> 113.2 22.86 1 34 0 0
#> 37.2 12.52 1 57 1 0
#> 50.1 10.02 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 40.1 18.00 1 28 1 0
#> 24 23.89 1 38 0 0
#> 29 15.45 1 68 1 0
#> 100 16.07 1 60 0 0
#> 64 24.00 0 43 0 0
#> 121 24.00 0 57 1 0
#> 141 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 200 24.00 0 64 0 0
#> 2 24.00 0 9 0 0
#> 95 24.00 0 68 0 1
#> 151 24.00 0 42 0 0
#> 121.1 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 102 24.00 0 49 0 0
#> 33 24.00 0 53 0 0
#> 160 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 185 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 31 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 162 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 137 24.00 0 45 1 0
#> 47 24.00 0 38 0 1
#> 112 24.00 0 61 0 0
#> 17 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 46 24.00 0 71 0 0
#> 160.1 24.00 0 31 1 0
#> 151.1 24.00 0 42 0 0
#> 1 24.00 0 23 1 0
#> 73.1 24.00 0 NA 0 1
#> 19 24.00 0 57 0 1
#> 102.1 24.00 0 49 0 0
#> 1.1 24.00 0 23 1 0
#> 12.1 24.00 0 63 0 0
#> 147 24.00 0 76 1 0
#> 147.1 24.00 0 76 1 0
#> 182 24.00 0 35 0 0
#> 146 24.00 0 63 1 0
#> 67.1 24.00 0 25 0 0
#> 71 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 151.2 24.00 0 42 0 0
#> 122 24.00 0 66 0 0
#> 1.2 24.00 0 23 1 0
#> 75.1 24.00 0 21 1 0
#> 162.1 24.00 0 51 0 0
#> 75.2 24.00 0 21 1 0
#> 186 24.00 0 45 1 0
#> 80 24.00 0 41 0 0
#> 84.1 24.00 0 39 0 1
#> 73.2 24.00 0 NA 0 1
#> 12.2 24.00 0 63 0 0
#> 95.1 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 196 24.00 0 19 0 0
#> 120 24.00 0 68 0 1
#> 172 24.00 0 41 0 0
#> 174 24.00 0 49 1 0
#> 151.3 24.00 0 42 0 0
#> 147.2 24.00 0 76 1 0
#> 126 24.00 0 48 0 0
#> 182.1 24.00 0 35 0 0
#> 22 24.00 0 52 1 0
#> 146.1 24.00 0 63 1 0
#> 3 24.00 0 31 1 0
#> 126.1 24.00 0 48 0 0
#> 95.2 24.00 0 68 0 1
#> 151.4 24.00 0 42 0 0
#> 160.2 24.00 0 31 1 0
#> 1.3 24.00 0 23 1 0
#> 104 24.00 0 50 1 0
#> 138 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 38 24.00 0 31 1 0
#> 126.2 24.00 0 48 0 0
#> 191 24.00 0 60 0 1
#> 146.2 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 200.1 24.00 0 64 0 0
#> 27 24.00 0 63 1 0
#> 165 24.00 0 47 0 0
#> 148 24.00 0 61 1 0
#> 126.3 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 71.1 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.199 NA NA NA
#> 2 age, Cure model 0.00442 NA NA NA
#> 3 grade_ii, Cure model -0.103 NA NA NA
#> 4 grade_iii, Cure model 0.799 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00216 NA NA NA
#> 2 grade_ii, Survival model 0.756 NA NA NA
#> 3 grade_iii, Survival model 0.253 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.198729 0.004423 -0.103025 0.799220
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.2
#> Residual Deviance: 248.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.19872889 0.00442292 -0.10302469 0.79922017
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002156184 0.756444498 0.252567593
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.150059915 0.136516070 0.455080399 0.716311218 0.759938169 0.680906501
#> [7] 0.201484355 0.455080399 0.802026291 0.776741458 0.311105138 0.332728983
#> [13] 0.495159642 0.826975299 0.843486178 0.961745284 0.992384458 0.907150633
#> [19] 0.689823280 0.645562235 0.364108328 0.922752610 0.636531121 0.095619028
#> [25] 0.930576509 0.946223778 0.228231090 0.255326646 0.026119591 0.255326646
#> [31] 0.150059915 0.110373148 0.689823280 0.759938169 0.600653593 0.689823280
#> [37] 0.645562235 0.374428228 0.969441629 0.353731467 0.026119591 0.891304338
#> [43] 0.415172446 0.627478396 0.054135263 0.716311218 0.553507080 0.415172446
#> [49] 0.977131006 0.054135263 0.883362872 0.600653593 0.810479010 0.187840257
#> [55] 0.810479010 0.843486178 0.110373148 0.859718680 0.288769944 0.405059116
#> [61] 0.343382105 0.311105138 0.891304338 0.553507080 0.953987833 0.600653593
#> [67] 0.645562235 0.201484355 0.826975299 0.543955809 0.776741458 0.534367986
#> [73] 0.484965421 0.505337865 0.255326646 0.444951485 0.859718680 0.394901843
#> [79] 0.384776187 0.984761532 0.938405061 0.907150633 0.299976188 0.415172446
#> [85] 0.581859199 0.455080399 0.572339685 0.581859199 0.515324092 0.733997775
#> [91] 0.242095470 0.733997775 0.793579865 0.150059915 0.859718680 0.080655892
#> [97] 0.515324092 0.008822457 0.751313711 0.671971207 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 113 92 179 39 18 26 66 179.1 81 157 90 32 51
#> 22.86 22.92 18.63 15.59 15.21 15.77 22.13 18.63 14.06 15.10 20.94 20.90 18.23
#> 14 140 149 127 107 6 85 128 159 181 164 10 145
#> 12.89 12.68 8.37 3.53 11.18 15.64 16.44 20.35 10.55 16.46 23.60 10.53 10.07
#> 175 139 78 139.1 113.1 69 6.1 18.1 106 6.2 192 150 77
#> 21.91 21.49 23.88 21.49 22.86 23.23 15.64 15.21 16.67 15.64 16.44 20.33 7.27
#> 68 78.1 56 58 130 86 39.1 111 58.1 25 86.1 42 106.1
#> 20.62 23.88 12.21 19.34 16.47 23.81 15.59 17.45 19.34 6.32 23.81 12.43 16.67
#> 123 15 123.1 140.1 69.1 37 153 170 190 90.1 56.1 111.1 16
#> 13.00 22.68 13.00 12.68 23.23 12.52 21.33 19.54 20.81 20.94 12.21 17.45 8.71
#> 106.2 85.1 66.1 14.1 117 157.1 110 88 41 139.2 97 37.1 105
#> 16.67 16.44 22.13 12.89 17.46 15.10 17.56 18.37 18.02 21.49 19.14 12.52 19.75
#> 158 91 93 107.1 99 58.2 45 179.2 30 45.1 40 167 197
#> 20.14 5.33 10.33 11.18 21.19 19.34 17.42 18.63 17.43 17.42 18.00 15.55 21.60
#> 167.1 96 113.2 37.2 168 40.1 24 29 100 64 121 141 9
#> 15.55 14.54 22.86 12.52 23.72 18.00 23.89 15.45 16.07 24.00 24.00 24.00 24.00
#> 200 2 95 151 121.1 178 102 33 160 178.1 185 67 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 162 84 137 47 112 17 12 46 160.1 151.1 1 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 1.1 12.1 147 147.1 182 146 67.1 71 7 151.2 122 1.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 162.1 75.2 186 80 84.1 12.2 95.1 143 28 196 120 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 151.3 147.2 126 182.1 22 146.1 3 126.1 95.2 151.4 160.2 1.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 138 198 38 126.2 191 146.2 116 200.1 27 165 148 126.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 71.1 193
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[15]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0107474 0.6218955 0.3667109
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.8785668 0.0107998 0.3409388
#> grade_iii, Cure model
#> 1.2278441
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 111 17.45 1 47 0 1
#> 107 11.18 1 54 1 0
#> 181 16.46 1 45 0 1
#> 136 21.83 1 43 0 1
#> 110 17.56 1 65 0 1
#> 187 9.92 1 39 1 0
#> 24 23.89 1 38 0 0
#> 23 16.92 1 61 0 0
#> 59 10.16 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 92 22.92 1 47 0 1
#> 125.1 15.65 1 67 1 0
#> 40 18.00 1 28 1 0
#> 79 16.23 1 54 1 0
#> 16 8.71 1 71 0 1
#> 16.1 8.71 1 71 0 1
#> 36 21.19 1 48 0 1
#> 154 12.63 1 20 1 0
#> 184 17.77 1 38 0 0
#> 36.1 21.19 1 48 0 1
#> 8 18.43 1 32 0 0
#> 136.1 21.83 1 43 0 1
#> 45 17.42 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 181.1 16.46 1 45 0 1
#> 5 16.43 1 51 0 1
#> 42 12.43 1 49 0 1
#> 68 20.62 1 44 0 0
#> 43 12.10 1 61 0 1
#> 5.1 16.43 1 51 0 1
#> 130 16.47 1 53 0 1
#> 155 13.08 1 26 0 0
#> 81 14.06 1 34 0 0
#> 37 12.52 1 57 1 0
#> 157 15.10 1 47 0 0
#> 40.1 18.00 1 28 1 0
#> 23.1 16.92 1 61 0 0
#> 88 18.37 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 16.2 8.71 1 71 0 1
#> 29 15.45 1 68 1 0
#> 24.1 23.89 1 38 0 0
#> 70 7.38 1 30 1 0
#> 56 12.21 1 60 0 0
#> 92.1 22.92 1 47 0 1
#> 150 20.33 1 48 0 0
#> 37.1 12.52 1 57 1 0
#> 45.1 17.42 1 54 0 1
#> 189.1 10.51 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 40.2 18.00 1 28 1 0
#> 36.2 21.19 1 48 0 1
#> 96 14.54 1 33 0 1
#> 171 16.57 1 41 0 1
#> 32 20.90 1 37 1 0
#> 4 17.64 1 NA 0 1
#> 129 23.41 1 53 1 0
#> 183 9.24 1 67 1 0
#> 111.1 17.45 1 47 0 1
#> 181.2 16.46 1 45 0 1
#> 134 17.81 1 47 1 0
#> 13 14.34 1 54 0 1
#> 59.1 10.16 1 NA 1 0
#> 32.1 20.90 1 37 1 0
#> 59.2 10.16 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 25 6.32 1 34 1 0
#> 4.1 17.64 1 NA 0 1
#> 32.2 20.90 1 37 1 0
#> 10 10.53 1 34 0 0
#> 171.1 16.57 1 41 0 1
#> 107.1 11.18 1 54 1 0
#> 29.1 15.45 1 68 1 0
#> 107.2 11.18 1 54 1 0
#> 96.1 14.54 1 33 0 1
#> 99 21.19 1 38 0 1
#> 188 16.16 1 46 0 1
#> 96.2 14.54 1 33 0 1
#> 4.2 17.64 1 NA 0 1
#> 195 11.76 1 NA 1 0
#> 13.1 14.34 1 54 0 1
#> 81.1 14.06 1 34 0 0
#> 166.1 19.98 1 48 0 0
#> 43.1 12.10 1 61 0 1
#> 189.2 10.51 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 91 5.33 1 61 0 1
#> 51 18.23 1 83 0 1
#> 133 14.65 1 57 0 0
#> 140 12.68 1 59 1 0
#> 110.1 17.56 1 65 0 1
#> 61 10.12 1 36 0 1
#> 15 22.68 1 48 0 0
#> 177 12.53 1 75 0 0
#> 149 8.37 1 33 1 0
#> 192 16.44 1 31 1 0
#> 51.1 18.23 1 83 0 1
#> 8.1 18.43 1 32 0 0
#> 134.1 17.81 1 47 1 0
#> 5.2 16.43 1 51 0 1
#> 150.1 20.33 1 48 0 0
#> 108 18.29 1 39 0 1
#> 5.3 16.43 1 51 0 1
#> 171.2 16.57 1 41 0 1
#> 60 13.15 1 38 1 0
#> 128 20.35 1 35 0 1
#> 168 23.72 1 70 0 0
#> 158 20.14 1 74 1 0
#> 124 9.73 1 NA 1 0
#> 134.2 17.81 1 47 1 0
#> 128.1 20.35 1 35 0 1
#> 48 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 102 24.00 0 49 0 0
#> 186 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 102.1 24.00 0 49 0 0
#> 156 24.00 0 50 1 0
#> 22 24.00 0 52 1 0
#> 34.1 24.00 0 36 0 0
#> 62 24.00 0 71 0 0
#> 122 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 2 24.00 0 9 0 0
#> 54 24.00 0 53 1 0
#> 144 24.00 0 28 0 1
#> 156.1 24.00 0 50 1 0
#> 138 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 33 24.00 0 53 0 0
#> 163.1 24.00 0 66 0 0
#> 121 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 162 24.00 0 51 0 0
#> 121.1 24.00 0 57 1 0
#> 22.1 24.00 0 52 1 0
#> 141 24.00 0 44 1 0
#> 144.1 24.00 0 28 0 1
#> 64 24.00 0 43 0 0
#> 53 24.00 0 32 0 1
#> 185 24.00 0 44 1 0
#> 186.1 24.00 0 45 1 0
#> 3 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 143 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 31 24.00 0 36 0 1
#> 54.1 24.00 0 53 1 0
#> 119 24.00 0 17 0 0
#> 161.1 24.00 0 45 0 0
#> 95 24.00 0 68 0 1
#> 174 24.00 0 49 1 0
#> 144.2 24.00 0 28 0 1
#> 103 24.00 0 56 1 0
#> 7 24.00 0 37 1 0
#> 33.1 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 46 24.00 0 71 0 0
#> 74 24.00 0 43 0 1
#> 198 24.00 0 66 0 1
#> 178.1 24.00 0 52 1 0
#> 46.1 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 71 24.00 0 51 0 0
#> 185.1 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 22.2 24.00 0 52 1 0
#> 182 24.00 0 35 0 0
#> 174.1 24.00 0 49 1 0
#> 115 24.00 0 NA 1 0
#> 83 24.00 0 6 0 0
#> 174.2 24.00 0 49 1 0
#> 135 24.00 0 58 1 0
#> 104 24.00 0 50 1 0
#> 137 24.00 0 45 1 0
#> 53.1 24.00 0 32 0 1
#> 31.1 24.00 0 36 0 1
#> 94 24.00 0 51 0 1
#> 47 24.00 0 38 0 1
#> 165.1 24.00 0 47 0 0
#> 120 24.00 0 68 0 1
#> 71.1 24.00 0 51 0 0
#> 80.1 24.00 0 41 0 0
#> 109 24.00 0 48 0 0
#> 53.2 24.00 0 32 0 1
#> 74.1 24.00 0 43 0 1
#> 53.3 24.00 0 32 0 1
#> 163.2 24.00 0 66 0 0
#> 119.1 24.00 0 17 0 0
#> 2.1 24.00 0 9 0 0
#> 75.1 24.00 0 21 1 0
#> 73 24.00 0 NA 0 1
#> 19 24.00 0 57 0 1
#> 112 24.00 0 61 0 0
#> 138.1 24.00 0 44 1 0
#> 120.1 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.879 NA NA NA
#> 2 age, Cure model 0.0108 NA NA NA
#> 3 grade_ii, Cure model 0.341 NA NA NA
#> 4 grade_iii, Cure model 1.23 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0107 NA NA NA
#> 2 grade_ii, Survival model 0.622 NA NA NA
#> 3 grade_iii, Survival model 0.367 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.8786 0.0108 0.3409 1.2278
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 243.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.8785668 0.0107998 0.3409388 1.2278441
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0107474 0.6218955 0.3667109
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6932626 0.9412127 0.7590605 0.3379548 0.6717606 0.9629107 0.1020961
#> [8] 0.7205006 0.8232891 0.2715800 0.8232891 0.6175856 0.8120225 0.9714439
#> [15] 0.9714439 0.3745320 0.9042368 0.6642371 0.3745320 0.5621538 0.3379548
#> [22] 0.7070885 0.7590605 0.7892535 0.9230338 0.4780566 0.9322233 0.7892535
#> [29] 0.7527385 0.8945297 0.8797740 0.9137803 0.8444299 0.6175856 0.7205006
#> [36] 0.5813445 0.5426904 0.9714439 0.8340515 0.1020961 0.9878701 0.9276389
#> [43] 0.2715800 0.5114421 0.9137803 0.7070885 0.7772643 0.6175856 0.3745320
#> [50] 0.8547717 0.7336854 0.4301619 0.2411769 0.9672039 0.6932626 0.7590605
#> [57] 0.6417943 0.8698644 0.4301619 0.4662897 0.9919417 0.4301619 0.9542314
#> [64] 0.7336854 0.9412127 0.8340515 0.9412127 0.8547717 0.3745320 0.8176823
#> [71] 0.8547717 0.8698644 0.8797740 0.5426904 0.9322233 0.6861155 0.9959853
#> [78] 0.6003053 0.8496141 0.8994162 0.6717606 0.9585821 0.3159898 0.9090241
#> [85] 0.9837719 0.7772643 0.6003053 0.5621538 0.6417943 0.7892535 0.5114421
#> [92] 0.5909157 0.7892535 0.7336854 0.8896347 0.4896511 0.1984678 0.5326240
#> [99] 0.6417943 0.4896511 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 111 107 181 136 110 187 24 23 125 92 125.1 40 79
#> 17.45 11.18 16.46 21.83 17.56 9.92 23.89 16.92 15.65 22.92 15.65 18.00 16.23
#> 16 16.1 36 154 184 36.1 8 136.1 45 181.1 5 42 68
#> 8.71 8.71 21.19 12.63 17.77 21.19 18.43 21.83 17.42 16.46 16.43 12.43 20.62
#> 43 5.1 130 155 81 37 157 40.1 23.1 88 166 16.2 29
#> 12.10 16.43 16.47 13.08 14.06 12.52 15.10 18.00 16.92 18.37 19.98 8.71 15.45
#> 24.1 70 56 92.1 150 37.1 45.1 85 40.2 36.2 96 171 32
#> 23.89 7.38 12.21 22.92 20.33 12.52 17.42 16.44 18.00 21.19 14.54 16.57 20.90
#> 129 183 111.1 181.2 134 13 32.1 190 25 32.2 10 171.1 107.1
#> 23.41 9.24 17.45 16.46 17.81 14.34 20.90 20.81 6.32 20.90 10.53 16.57 11.18
#> 29.1 107.2 96.1 99 188 96.2 13.1 81.1 166.1 43.1 117 91 51
#> 15.45 11.18 14.54 21.19 16.16 14.54 14.34 14.06 19.98 12.10 17.46 5.33 18.23
#> 133 140 110.1 61 15 177 149 192 51.1 8.1 134.1 5.2 150.1
#> 14.65 12.68 17.56 10.12 22.68 12.53 8.37 16.44 18.23 18.43 17.81 16.43 20.33
#> 108 5.3 171.2 60 128 168 158 134.2 128.1 48 152 34 102
#> 18.29 16.43 16.57 13.15 20.35 23.72 20.14 17.81 20.35 24.00 24.00 24.00 24.00
#> 186 165 102.1 156 22 34.1 62 122 80 2 54 144 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 163 161 33 163.1 121 118 75 162 121.1 22.1 141 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 53 185 186.1 3 142 143 178 31 54.1 119 161.1 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 144.2 103 7 33.1 82 46 74 198 178.1 46.1 146 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 200 22.2 182 174.1 83 174.2 135 104 137 53.1 31.1 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 165.1 120 71.1 80.1 109 53.2 74.1 53.3 163.2 119.1 2.1 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 112 138.1 120.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[16]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009795989 0.822407749 0.557290204
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.194863089 -0.001822732 0.110206064
#> grade_iii, Cure model
#> 1.360833525
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 153 21.33 1 55 1 0
#> 97 19.14 1 65 0 1
#> 164 23.60 1 76 0 1
#> 133 14.65 1 57 0 0
#> 89 11.44 1 NA 0 0
#> 79 16.23 1 54 1 0
#> 36 21.19 1 48 0 1
#> 60 13.15 1 38 1 0
#> 41 18.02 1 40 1 0
#> 97.1 19.14 1 65 0 1
#> 91 5.33 1 61 0 1
#> 89.1 11.44 1 NA 0 0
#> 124 9.73 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 77 7.27 1 67 0 1
#> 96 14.54 1 33 0 1
#> 86 23.81 1 58 0 1
#> 61 10.12 1 36 0 1
#> 51 18.23 1 83 0 1
#> 180 14.82 1 37 0 0
#> 78 23.88 1 43 0 0
#> 61.1 10.12 1 36 0 1
#> 92 22.92 1 47 0 1
#> 92.1 22.92 1 47 0 1
#> 68 20.62 1 44 0 0
#> 168 23.72 1 70 0 0
#> 190 20.81 1 42 1 0
#> 59 10.16 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 167 15.55 1 56 1 0
#> 24 23.89 1 38 0 0
#> 39 15.59 1 37 0 1
#> 128 20.35 1 35 0 1
#> 36.1 21.19 1 48 0 1
#> 36.2 21.19 1 48 0 1
#> 14 12.89 1 21 0 0
#> 111 17.45 1 47 0 1
#> 183 9.24 1 67 1 0
#> 179 18.63 1 42 0 0
#> 86.1 23.81 1 58 0 1
#> 113 22.86 1 34 0 0
#> 14.1 12.89 1 21 0 0
#> 49 12.19 1 48 1 0
#> 181 16.46 1 45 0 1
#> 133.1 14.65 1 57 0 0
#> 4 17.64 1 NA 0 1
#> 37.1 12.52 1 57 1 0
#> 154 12.63 1 20 1 0
#> 128.1 20.35 1 35 0 1
#> 24.1 23.89 1 38 0 0
#> 63 22.77 1 31 1 0
#> 184 17.77 1 38 0 0
#> 168.1 23.72 1 70 0 0
#> 91.1 5.33 1 61 0 1
#> 129 23.41 1 53 1 0
#> 157 15.10 1 47 0 0
#> 43 12.10 1 61 0 1
#> 96.1 14.54 1 33 0 1
#> 123 13.00 1 44 1 0
#> 133.2 14.65 1 57 0 0
#> 175 21.91 1 43 0 0
#> 5 16.43 1 51 0 1
#> 154.1 12.63 1 20 1 0
#> 189 10.51 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 155 13.08 1 26 0 0
#> 37.2 12.52 1 57 1 0
#> 125 15.65 1 67 1 0
#> 26 15.77 1 49 0 1
#> 128.2 20.35 1 35 0 1
#> 61.2 10.12 1 36 0 1
#> 194 22.40 1 38 0 1
#> 96.2 14.54 1 33 0 1
#> 58 19.34 1 39 0 0
#> 180.1 14.82 1 37 0 0
#> 123.1 13.00 1 44 1 0
#> 153.1 21.33 1 55 1 0
#> 25 6.32 1 34 1 0
#> 96.3 14.54 1 33 0 1
#> 61.3 10.12 1 36 0 1
#> 181.1 16.46 1 45 0 1
#> 189.1 10.51 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 194.1 22.40 1 38 0 1
#> 50 10.02 1 NA 1 0
#> 113.1 22.86 1 34 0 0
#> 30 17.43 1 78 0 0
#> 63.1 22.77 1 31 1 0
#> 155.1 13.08 1 26 0 0
#> 164.1 23.60 1 76 0 1
#> 181.2 16.46 1 45 0 1
#> 150.1 20.33 1 48 0 0
#> 194.2 22.40 1 38 0 1
#> 15 22.68 1 48 0 0
#> 125.1 15.65 1 67 1 0
#> 39.1 15.59 1 37 0 1
#> 78.1 23.88 1 43 0 0
#> 199 19.81 1 NA 0 1
#> 106 16.67 1 49 1 0
#> 61.4 10.12 1 36 0 1
#> 125.2 15.65 1 67 1 0
#> 168.2 23.72 1 70 0 0
#> 93 10.33 1 52 0 1
#> 139 21.49 1 63 1 0
#> 140 12.68 1 59 1 0
#> 93.1 10.33 1 52 0 1
#> 111.1 17.45 1 47 0 1
#> 40 18.00 1 28 1 0
#> 130 16.47 1 53 0 1
#> 97.2 19.14 1 65 0 1
#> 23 16.92 1 61 0 0
#> 30.1 17.43 1 78 0 0
#> 7 24.00 0 37 1 0
#> 12 24.00 0 63 0 0
#> 74 24.00 0 43 0 1
#> 116 24.00 0 58 0 1
#> 27 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 12.1 24.00 0 63 0 0
#> 156 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 71 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 162.1 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 132 24.00 0 55 0 0
#> 87 24.00 0 27 0 0
#> 174 24.00 0 49 1 0
#> 174.1 24.00 0 49 1 0
#> 174.2 24.00 0 49 1 0
#> 137 24.00 0 45 1 0
#> 1 24.00 0 23 1 0
#> 75 24.00 0 21 1 0
#> 48 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 146.1 24.00 0 63 1 0
#> 9 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 109 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 165 24.00 0 47 0 0
#> 64 24.00 0 43 0 0
#> 138 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 200 24.00 0 64 0 0
#> 83 24.00 0 6 0 0
#> 142 24.00 0 53 0 0
#> 34 24.00 0 36 0 0
#> 102 24.00 0 49 0 0
#> 112 24.00 0 61 0 0
#> 144 24.00 0 28 0 1
#> 196 24.00 0 19 0 0
#> 75.1 24.00 0 21 1 0
#> 109.1 24.00 0 48 0 0
#> 62 24.00 0 71 0 0
#> 34.1 24.00 0 36 0 0
#> 196.1 24.00 0 19 0 0
#> 142.1 24.00 0 53 0 0
#> 120 24.00 0 68 0 1
#> 141 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 87.1 24.00 0 27 0 0
#> 120.1 24.00 0 68 0 1
#> 200.1 24.00 0 64 0 0
#> 193 24.00 0 45 0 1
#> 38 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 67 24.00 0 25 0 0
#> 22 24.00 0 52 1 0
#> 62.1 24.00 0 71 0 0
#> 118 24.00 0 44 1 0
#> 54.1 24.00 0 53 1 0
#> 65 24.00 0 57 1 0
#> 84 24.00 0 39 0 1
#> 95.1 24.00 0 68 0 1
#> 198 24.00 0 66 0 1
#> 38.1 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 172 24.00 0 41 0 0
#> 141.1 24.00 0 44 1 0
#> 172.1 24.00 0 41 0 0
#> 28.1 24.00 0 67 1 0
#> 46 24.00 0 71 0 0
#> 142.2 24.00 0 53 0 0
#> 3 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 119 24.00 0 17 0 0
#> 112.1 24.00 0 61 0 0
#> 137.1 24.00 0 45 1 0
#> 178 24.00 0 52 1 0
#> 35 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 200.2 24.00 0 64 0 0
#> 53 24.00 0 32 0 1
#> 12.2 24.00 0 63 0 0
#> 182 24.00 0 35 0 0
#> 80 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 196.2 24.00 0 19 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.195 NA NA NA
#> 2 age, Cure model -0.00182 NA NA NA
#> 3 grade_ii, Cure model 0.110 NA NA NA
#> 4 grade_iii, Cure model 1.36 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00980 NA NA NA
#> 2 grade_ii, Survival model 0.822 NA NA NA
#> 3 grade_iii, Survival model 0.557 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.194863 -0.001823 0.110206 1.360834
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262.4
#> Residual Deviance: 246.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.194863089 -0.001822732 0.110206064 1.360833525
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009795989 0.822407749 0.557290204
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.238842564 0.365373584 0.078129406 0.674301086 0.565916078 0.258764499
#> [7] 0.743400531 0.425305236 0.365373584 0.981463438 0.962795898 0.704286694
#> [13] 0.031331466 0.907503859 0.415053483 0.654538490 0.014900026 0.907503859
#> [19] 0.112424234 0.112424234 0.297608388 0.048084539 0.287769622 0.841309061
#> [25] 0.634862381 0.003491637 0.615298790 0.307562401 0.258764499 0.258764499
#> [31] 0.792642886 0.455398655 0.953442421 0.394732285 0.031331466 0.133990688
#> [37] 0.792642886 0.869621632 0.526013414 0.674301086 0.841309061 0.822130461
#> [43] 0.307562401 0.003491637 0.156593651 0.445377391 0.048084539 0.981463438
#> [49] 0.100836757 0.644672737 0.879119473 0.704286694 0.773092545 0.674301086
#> [55] 0.217792395 0.555811361 0.822130461 0.404858570 0.753302510 0.841309061
#> [61] 0.585989167 0.575959646 0.307562401 0.907503859 0.188041016 0.704286694
#> [67] 0.355376381 0.654538490 0.773092545 0.238842564 0.972157952 0.704286694
#> [73] 0.907503859 0.526013414 0.335835298 0.188041016 0.133990688 0.475133428
#> [79] 0.156593651 0.753302510 0.078129406 0.526013414 0.335835298 0.188041016
#> [85] 0.177183943 0.585989167 0.615298790 0.014900026 0.505607704 0.907503859
#> [91] 0.585989167 0.048084539 0.888621366 0.228372686 0.812283320 0.888621366
#> [97] 0.455398655 0.435425730 0.515814475 0.365373584 0.495316109 0.475133428
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 153 97 164 133 79 36 60 41 97.1 91 77 96 86
#> 21.33 19.14 23.60 14.65 16.23 21.19 13.15 18.02 19.14 5.33 7.27 14.54 23.81
#> 61 51 180 78 61.1 92 92.1 68 168 190 37 167 24
#> 10.12 18.23 14.82 23.88 10.12 22.92 22.92 20.62 23.72 20.81 12.52 15.55 23.89
#> 39 128 36.1 36.2 14 111 183 179 86.1 113 14.1 49 181
#> 15.59 20.35 21.19 21.19 12.89 17.45 9.24 18.63 23.81 22.86 12.89 12.19 16.46
#> 133.1 37.1 154 128.1 24.1 63 184 168.1 91.1 129 157 43 96.1
#> 14.65 12.52 12.63 20.35 23.89 22.77 17.77 23.72 5.33 23.41 15.10 12.10 14.54
#> 123 133.2 175 5 154.1 8 155 37.2 125 26 128.2 61.2 194
#> 13.00 14.65 21.91 16.43 12.63 18.43 13.08 12.52 15.65 15.77 20.35 10.12 22.40
#> 96.2 58 180.1 123.1 153.1 25 96.3 61.3 181.1 150 194.1 113.1 30
#> 14.54 19.34 14.82 13.00 21.33 6.32 14.54 10.12 16.46 20.33 22.40 22.86 17.43
#> 63.1 155.1 164.1 181.2 150.1 194.2 15 125.1 39.1 78.1 106 61.4 125.2
#> 22.77 13.08 23.60 16.46 20.33 22.40 22.68 15.65 15.59 23.88 16.67 10.12 15.65
#> 168.2 93 139 140 93.1 111.1 40 130 97.2 23 30.1 7 12
#> 23.72 10.33 21.49 12.68 10.33 17.45 18.00 16.47 19.14 16.92 17.43 24.00 24.00
#> 74 116 27 185 162 12.1 156 146 71 17 162.1 19 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 174 174.1 174.2 137 1 75 48 191 146.1 9 54 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 165 64 138 28 200 83 142 34 102 112 144 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 109.1 62 34.1 196.1 142.1 120 141 163 87.1 120.1 200.1 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 82 67 22 62.1 118 54.1 65 84 95.1 198 38.1 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 141.1 172.1 28.1 46 142.2 3 131 119 112.1 137.1 178 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 200.2 53 12.2 182 80 72 196.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[17]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002966537 0.605287201 0.681412235
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.110815874 0.007078194 -0.470005547
#> grade_iii, Cure model
#> 0.501348048
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 133 14.65 1 57 0 0
#> 113 22.86 1 34 0 0
#> 129 23.41 1 53 1 0
#> 50 10.02 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 18 15.21 1 49 1 0
#> 188 16.16 1 46 0 1
#> 97 19.14 1 65 0 1
#> 79 16.23 1 54 1 0
#> 78 23.88 1 43 0 0
#> 139 21.49 1 63 1 0
#> 15 22.68 1 48 0 0
#> 49 12.19 1 48 1 0
#> 93 10.33 1 52 0 1
#> 155 13.08 1 26 0 0
#> 154 12.63 1 20 1 0
#> 16 8.71 1 71 0 1
#> 111 17.45 1 47 0 1
#> 25 6.32 1 34 1 0
#> 129.1 23.41 1 53 1 0
#> 106 16.67 1 49 1 0
#> 184 17.77 1 38 0 0
#> 69 23.23 1 25 0 1
#> 117 17.46 1 26 0 1
#> 168.1 23.72 1 70 0 0
#> 117.1 17.46 1 26 0 1
#> 57 14.46 1 45 0 1
#> 189 10.51 1 NA 1 0
#> 25.1 6.32 1 34 1 0
#> 180 14.82 1 37 0 0
#> 69.1 23.23 1 25 0 1
#> 23 16.92 1 61 0 0
#> 66 22.13 1 53 0 0
#> 113.1 22.86 1 34 0 0
#> 113.2 22.86 1 34 0 0
#> 134 17.81 1 47 1 0
#> 194 22.40 1 38 0 1
#> 127 3.53 1 62 0 1
#> 23.1 16.92 1 61 0 0
#> 187 9.92 1 39 1 0
#> 169 22.41 1 46 0 0
#> 105 19.75 1 60 0 0
#> 183 9.24 1 67 1 0
#> 177 12.53 1 75 0 0
#> 61 10.12 1 36 0 1
#> 18.1 15.21 1 49 1 0
#> 150 20.33 1 48 0 0
#> 41 18.02 1 40 1 0
#> 101 9.97 1 10 0 1
#> 195 11.76 1 NA 1 0
#> 66.1 22.13 1 53 0 0
#> 157 15.10 1 47 0 0
#> 167 15.55 1 56 1 0
#> 13 14.34 1 54 0 1
#> 66.2 22.13 1 53 0 0
#> 23.2 16.92 1 61 0 0
#> 92 22.92 1 47 0 1
#> 113.3 22.86 1 34 0 0
#> 60 13.15 1 38 1 0
#> 125 15.65 1 67 1 0
#> 184.1 17.77 1 38 0 0
#> 97.1 19.14 1 65 0 1
#> 59 10.16 1 NA 1 0
#> 61.1 10.12 1 36 0 1
#> 136 21.83 1 43 0 1
#> 60.1 13.15 1 38 1 0
#> 114 13.68 1 NA 0 0
#> 45 17.42 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 93.1 10.33 1 52 0 1
#> 149 8.37 1 33 1 0
#> 59.1 10.16 1 NA 1 0
#> 16.1 8.71 1 71 0 1
#> 171 16.57 1 41 0 1
#> 79.1 16.23 1 54 1 0
#> 114.1 13.68 1 NA 0 0
#> 167.1 15.55 1 56 1 0
#> 57.1 14.46 1 45 0 1
#> 139.1 21.49 1 63 1 0
#> 155.1 13.08 1 26 0 0
#> 179 18.63 1 42 0 0
#> 154.1 12.63 1 20 1 0
#> 96 14.54 1 33 0 1
#> 91 5.33 1 61 0 1
#> 79.2 16.23 1 54 1 0
#> 43 12.10 1 61 0 1
#> 52 10.42 1 52 0 1
#> 197 21.60 1 69 1 0
#> 8 18.43 1 32 0 0
#> 166 19.98 1 48 0 0
#> 13.1 14.34 1 54 0 1
#> 183.1 9.24 1 67 1 0
#> 117.2 17.46 1 26 0 1
#> 157.1 15.10 1 47 0 0
#> 168.2 23.72 1 70 0 0
#> 113.4 22.86 1 34 0 0
#> 117.3 17.46 1 26 0 1
#> 6 15.64 1 39 0 0
#> 127.1 3.53 1 62 0 1
#> 125.1 15.65 1 67 1 0
#> 76 19.22 1 54 0 1
#> 129.2 23.41 1 53 1 0
#> 90 20.94 1 50 0 1
#> 5 16.43 1 51 0 1
#> 85 16.44 1 36 0 0
#> 57.2 14.46 1 45 0 1
#> 192 16.44 1 31 1 0
#> 133.1 14.65 1 57 0 0
#> 63 22.77 1 31 1 0
#> 85.1 16.44 1 36 0 0
#> 55 19.34 1 69 0 1
#> 14 12.89 1 21 0 0
#> 3 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 80 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 193 24.00 0 45 0 1
#> 160 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 7 24.00 0 37 1 0
#> 137 24.00 0 45 1 0
#> 173 24.00 0 19 0 1
#> 138 24.00 0 44 1 0
#> 3.1 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 165 24.00 0 47 0 0
#> 1 24.00 0 23 1 0
#> 103 24.00 0 56 1 0
#> 38 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 80.1 24.00 0 41 0 0
#> 162 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 148.1 24.00 0 61 1 0
#> 33 24.00 0 53 0 0
#> 138.1 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 7.1 24.00 0 37 1 0
#> 198.1 24.00 0 66 0 1
#> 46 24.00 0 71 0 0
#> 2 24.00 0 9 0 0
#> 109 24.00 0 48 0 0
#> 27 24.00 0 63 1 0
#> 162.1 24.00 0 51 0 0
#> 165.1 24.00 0 47 0 0
#> 120 24.00 0 68 0 1
#> 75 24.00 0 21 1 0
#> 198.2 24.00 0 66 0 1
#> 47 24.00 0 38 0 1
#> 75.1 24.00 0 21 1 0
#> 34 24.00 0 36 0 0
#> 152 24.00 0 36 0 1
#> 165.2 24.00 0 47 0 0
#> 193.1 24.00 0 45 0 1
#> 156 24.00 0 50 1 0
#> 62 24.00 0 71 0 0
#> 33.1 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 118 24.00 0 44 1 0
#> 3.2 24.00 0 31 1 0
#> 47.1 24.00 0 38 0 1
#> 27.1 24.00 0 63 1 0
#> 143 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 27.2 24.00 0 63 1 0
#> 20 24.00 0 46 1 0
#> 147 24.00 0 76 1 0
#> 118.1 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 162.2 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 119 24.00 0 17 0 0
#> 46.1 24.00 0 71 0 0
#> 161 24.00 0 45 0 0
#> 33.2 24.00 0 53 0 0
#> 160.1 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 176 24.00 0 43 0 1
#> 141 24.00 0 44 1 0
#> 198.3 24.00 0 66 0 1
#> 38.1 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 109.1 24.00 0 48 0 0
#> 75.2 24.00 0 21 1 0
#> 103.1 24.00 0 56 1 0
#> 144 24.00 0 28 0 1
#> 28 24.00 0 67 1 0
#> 144.1 24.00 0 28 0 1
#> 138.2 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 161.1 24.00 0 45 0 0
#> 44 24.00 0 56 0 0
#> 9.1 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 65 24.00 0 57 1 0
#> 11.1 24.00 0 42 0 1
#> 98 24.00 0 34 1 0
#> 20.1 24.00 0 46 1 0
#> 172 24.00 0 41 0 0
#> 163 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.111 NA NA NA
#> 2 age, Cure model 0.00708 NA NA NA
#> 3 grade_ii, Cure model -0.470 NA NA NA
#> 4 grade_iii, Cure model 0.501 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00297 NA NA NA
#> 2 grade_ii, Survival model 0.605 NA NA NA
#> 3 grade_iii, Survival model 0.681 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.110816 0.007078 -0.470006 0.501348
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 255.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.110815874 0.007078194 -0.470005547 0.501348048
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002966537 0.605287201 0.681412235
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.73912621 0.16999378 0.09143402 0.03701693 0.69878045 0.64924829
#> [7] 0.41229753 0.62411144 0.01188552 0.32792231 0.23645357 0.86346541
#> [13] 0.88606929 0.81767137 0.84070828 0.94412656 0.52695366 0.96533646
#> [19] 0.09143402 0.57165721 0.47174807 0.13295160 0.49117265 0.03701693
#> [25] 0.49117265 0.76341628 0.96533646 0.73100409 0.13295160 0.54498753
#> [31] 0.27172330 0.16999378 0.16999378 0.46197708 0.26021159 0.98624482
#> [37] 0.54498753 0.92263209 0.24829628 0.38083936 0.92985252 0.85584818
#> [43] 0.90081507 0.69878045 0.35964922 0.45208193 0.91537579 0.27172330
#> [49] 0.71486863 0.68247304 0.78686311 0.27172330 0.54498753 0.15777272
#> [55] 0.16999378 0.80236134 0.65765809 0.47174807 0.41229753 0.90081507
#> [61] 0.30541745 0.80236134 0.53602247 0.88606929 0.95827203 0.94412656
#> [67] 0.58060649 0.62411144 0.68247304 0.76341628 0.32792231 0.81767137
#> [73] 0.43203693 0.84070828 0.75533633 0.97928025 0.62411144 0.87104328
#> [79] 0.87857858 0.31676831 0.44204914 0.37022416 0.78686311 0.92985252
#> [85] 0.49117265 0.71486863 0.03701693 0.16999378 0.49117265 0.67415985
#> [91] 0.98624482 0.65765809 0.40199225 0.09143402 0.34911541 0.61541848
#> [97] 0.58945346 0.76341628 0.58945346 0.73912621 0.22468916 0.58945346
#> [103] 0.39150304 0.83300271 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 133 113 129 168 18 188 97 79 78 139 15 49 93
#> 14.65 22.86 23.41 23.72 15.21 16.16 19.14 16.23 23.88 21.49 22.68 12.19 10.33
#> 155 154 16 111 25 129.1 106 184 69 117 168.1 117.1 57
#> 13.08 12.63 8.71 17.45 6.32 23.41 16.67 17.77 23.23 17.46 23.72 17.46 14.46
#> 25.1 180 69.1 23 66 113.1 113.2 134 194 127 23.1 187 169
#> 6.32 14.82 23.23 16.92 22.13 22.86 22.86 17.81 22.40 3.53 16.92 9.92 22.41
#> 105 183 177 61 18.1 150 41 101 66.1 157 167 13 66.2
#> 19.75 9.24 12.53 10.12 15.21 20.33 18.02 9.97 22.13 15.10 15.55 14.34 22.13
#> 23.2 92 113.3 60 125 184.1 97.1 61.1 136 60.1 45 93.1 149
#> 16.92 22.92 22.86 13.15 15.65 17.77 19.14 10.12 21.83 13.15 17.42 10.33 8.37
#> 16.1 171 79.1 167.1 57.1 139.1 155.1 179 154.1 96 91 79.2 43
#> 8.71 16.57 16.23 15.55 14.46 21.49 13.08 18.63 12.63 14.54 5.33 16.23 12.10
#> 52 197 8 166 13.1 183.1 117.2 157.1 168.2 113.4 117.3 6 127.1
#> 10.42 21.60 18.43 19.98 14.34 9.24 17.46 15.10 23.72 22.86 17.46 15.64 3.53
#> 125.1 76 129.2 90 5 85 57.2 192 133.1 63 85.1 55 14
#> 15.65 19.22 23.41 20.94 16.43 16.44 14.46 16.44 14.65 22.77 16.44 19.34 12.89
#> 3 19 80 198 193 160 178 7 137 173 138 3.1 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 1 103 38 11 80.1 162 191 148.1 33 138.1 9 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.1 46 2 109 27 162.1 165.1 120 75 198.2 47 75.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 165.2 193.1 156 62 33.1 82 118 3.2 47.1 27.1 143 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.2 20 147 118.1 162.2 135 119 46.1 161 33.2 160.1 178.1 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 198.3 38.1 64 109.1 75.2 103.1 144 28 144.1 138.2 67 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 9.1 135.1 65 11.1 98 20.1 172 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[18]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0004855739 0.4601647988 0.0876565956
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.29033531 0.01036296 -0.74433153
#> grade_iii, Cure model
#> 0.85870060
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 79 16.23 1 54 1 0
#> 101 9.97 1 10 0 1
#> 85 16.44 1 36 0 0
#> 169 22.41 1 46 0 0
#> 14 12.89 1 21 0 0
#> 56 12.21 1 60 0 0
#> 49 12.19 1 48 1 0
#> 181 16.46 1 45 0 1
#> 166 19.98 1 48 0 0
#> 155 13.08 1 26 0 0
#> 57 14.46 1 45 0 1
#> 124 9.73 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 194 22.40 1 38 0 1
#> 63 22.77 1 31 1 0
#> 111 17.45 1 47 0 1
#> 81 14.06 1 34 0 0
#> 105 19.75 1 60 0 0
#> 26 15.77 1 49 0 1
#> 88 18.37 1 47 0 0
#> 145 10.07 1 65 1 0
#> 90 20.94 1 50 0 1
#> 86 23.81 1 58 0 1
#> 108 18.29 1 39 0 1
#> 86.1 23.81 1 58 0 1
#> 149 8.37 1 33 1 0
#> 5 16.43 1 51 0 1
#> 117 17.46 1 26 0 1
#> 42 12.43 1 49 0 1
#> 190 20.81 1 42 1 0
#> 108.1 18.29 1 39 0 1
#> 189 10.51 1 NA 1 0
#> 111.1 17.45 1 47 0 1
#> 184 17.77 1 38 0 0
#> 8 18.43 1 32 0 0
#> 32 20.90 1 37 1 0
#> 18 15.21 1 49 1 0
#> 88.1 18.37 1 47 0 0
#> 51 18.23 1 83 0 1
#> 195 11.76 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 150 20.33 1 48 0 0
#> 170 19.54 1 43 0 1
#> 106 16.67 1 49 1 0
#> 125 15.65 1 67 1 0
#> 155.1 13.08 1 26 0 0
#> 24 23.89 1 38 0 0
#> 105.1 19.75 1 60 0 0
#> 15 22.68 1 48 0 0
#> 77 7.27 1 67 0 1
#> 60 13.15 1 38 1 0
#> 117.1 17.46 1 26 0 1
#> 58 19.34 1 39 0 0
#> 76 19.22 1 54 0 1
#> 61 10.12 1 36 0 1
#> 97 19.14 1 65 0 1
#> 92 22.92 1 47 0 1
#> 79.1 16.23 1 54 1 0
#> 192 16.44 1 31 1 0
#> 189.1 10.51 1 NA 1 0
#> 51.1 18.23 1 83 0 1
#> 79.2 16.23 1 54 1 0
#> 81.1 14.06 1 34 0 0
#> 194.1 22.40 1 38 0 1
#> 125.1 15.65 1 67 1 0
#> 105.2 19.75 1 60 0 0
#> 69.1 23.23 1 25 0 1
#> 63.1 22.77 1 31 1 0
#> 26.1 15.77 1 49 0 1
#> 136 21.83 1 43 0 1
#> 30 17.43 1 78 0 0
#> 197 21.60 1 69 1 0
#> 85.1 16.44 1 36 0 0
#> 177 12.53 1 75 0 0
#> 175 21.91 1 43 0 0
#> 129 23.41 1 53 1 0
#> 69.2 23.23 1 25 0 1
#> 164 23.60 1 76 0 1
#> 111.2 17.45 1 47 0 1
#> 90.1 20.94 1 50 0 1
#> 188 16.16 1 46 0 1
#> 110 17.56 1 65 0 1
#> 107 11.18 1 54 1 0
#> 166.1 19.98 1 48 0 0
#> 66 22.13 1 53 0 0
#> 139 21.49 1 63 1 0
#> 89 11.44 1 NA 0 0
#> 113 22.86 1 34 0 0
#> 18.1 15.21 1 49 1 0
#> 69.3 23.23 1 25 0 1
#> 175.1 21.91 1 43 0 0
#> 26.2 15.77 1 49 0 1
#> 150.1 20.33 1 48 0 0
#> 81.2 14.06 1 34 0 0
#> 39.1 15.59 1 37 0 1
#> 168 23.72 1 70 0 0
#> 70 7.38 1 30 1 0
#> 175.2 21.91 1 43 0 0
#> 40 18.00 1 28 1 0
#> 169.1 22.41 1 46 0 0
#> 88.2 18.37 1 47 0 0
#> 130 16.47 1 53 0 1
#> 4 17.64 1 NA 0 1
#> 85.2 16.44 1 36 0 0
#> 10 10.53 1 34 0 0
#> 90.2 20.94 1 50 0 1
#> 76.1 19.22 1 54 0 1
#> 159 10.55 1 50 0 1
#> 42.1 12.43 1 49 0 1
#> 78 23.88 1 43 0 0
#> 108.2 18.29 1 39 0 1
#> 157 15.10 1 47 0 0
#> 98 24.00 0 34 1 0
#> 74 24.00 0 43 0 1
#> 138 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 28 24.00 0 67 1 0
#> 148 24.00 0 61 1 0
#> 38 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 118 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 46 24.00 0 71 0 0
#> 2 24.00 0 9 0 0
#> 161 24.00 0 45 0 0
#> 200 24.00 0 64 0 0
#> 54 24.00 0 53 1 0
#> 28.1 24.00 0 67 1 0
#> 64.1 24.00 0 43 0 0
#> 176 24.00 0 43 0 1
#> 80 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 121.1 24.00 0 57 1 0
#> 48 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 44 24.00 0 56 0 0
#> 95 24.00 0 68 0 1
#> 138.1 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 152 24.00 0 36 0 1
#> 47.1 24.00 0 38 0 1
#> 186 24.00 0 45 1 0
#> 74.1 24.00 0 43 0 1
#> 22 24.00 0 52 1 0
#> 112 24.00 0 61 0 0
#> 102 24.00 0 49 0 0
#> 137 24.00 0 45 1 0
#> 83 24.00 0 6 0 0
#> 34 24.00 0 36 0 0
#> 174.1 24.00 0 49 1 0
#> 75 24.00 0 21 1 0
#> 38.1 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 1 24.00 0 23 1 0
#> 21 24.00 0 47 0 0
#> 17 24.00 0 38 0 1
#> 137.1 24.00 0 45 1 0
#> 148.1 24.00 0 61 1 0
#> 119 24.00 0 17 0 0
#> 138.2 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 135 24.00 0 58 1 0
#> 82.1 24.00 0 34 0 0
#> 48.1 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 143 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 22.1 24.00 0 52 1 0
#> 53 24.00 0 32 0 1
#> 103 24.00 0 56 1 0
#> 12 24.00 0 63 0 0
#> 176.1 24.00 0 43 0 1
#> 178 24.00 0 52 1 0
#> 19 24.00 0 57 0 1
#> 3 24.00 0 31 1 0
#> 48.2 24.00 0 31 1 0
#> 148.2 24.00 0 61 1 0
#> 21.1 24.00 0 47 0 0
#> 87 24.00 0 27 0 0
#> 87.1 24.00 0 27 0 0
#> 121.2 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 196 24.00 0 19 0 0
#> 62 24.00 0 71 0 0
#> 33 24.00 0 53 0 0
#> 98.1 24.00 0 34 1 0
#> 31 24.00 0 36 0 1
#> 165 24.00 0 47 0 0
#> 21.2 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 20 24.00 0 46 1 0
#> 44.1 24.00 0 56 0 0
#> 44.2 24.00 0 56 0 0
#> 148.3 24.00 0 61 1 0
#> 65 24.00 0 57 1 0
#> 72.1 24.00 0 40 0 1
#> 144 24.00 0 28 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.290 NA NA NA
#> 2 age, Cure model 0.0104 NA NA NA
#> 3 grade_ii, Cure model -0.744 NA NA NA
#> 4 grade_iii, Cure model 0.859 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000486 NA NA NA
#> 2 grade_ii, Survival model 0.460 NA NA NA
#> 3 grade_iii, Survival model 0.0877 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.29034 0.01036 -0.74433 0.85870
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 267.3
#> Residual Deviance: 248.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.29033531 0.01036296 -0.74433153 0.85870060
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0004855739 0.4601647988 0.0876565956
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.694799647 0.966899827 0.650654355 0.191208868 0.874398998 0.908184497
#> [7] 0.916647892 0.641611104 0.366222162 0.857543528 0.815274604 0.099367446
#> [13] 0.211250174 0.161000154 0.587387705 0.823787531 0.384774722 0.729569120
#> [19] 0.468290254 0.958568457 0.300584841 0.037203486 0.495809259 0.037203486
#> [25] 0.975225005 0.685837112 0.569205276 0.891341064 0.338310995 0.495809259
#> [31] 0.587387705 0.550820518 0.458944266 0.328784694 0.789811647 0.468290254
#> [37] 0.523220455 0.772666462 0.347691425 0.412322693 0.623498971 0.755493790
#> [43] 0.857543528 0.008067548 0.384774722 0.180936358 0.991757259 0.849076071
#> [49] 0.569205276 0.421703050 0.431087330 0.950198158 0.449601219 0.138832570
#> [55] 0.694799647 0.650654355 0.523220455 0.694799647 0.823787531 0.211250174
#> [61] 0.755493790 0.384774722 0.099367446 0.161000154 0.729569120 0.270720403
#> [67] 0.614366165 0.280862439 0.650654355 0.882868577 0.241346940 0.087185991
#> [73] 0.099367446 0.074007831 0.587387705 0.300584841 0.720802377 0.560017249
#> [79] 0.925068695 0.366222162 0.231157664 0.290813323 0.149909469 0.789811647
#> [85] 0.099367446 0.241346940 0.729569120 0.347691425 0.823787531 0.772666462
#> [91] 0.060713144 0.983510633 0.241346940 0.541626598 0.191208868 0.468290254
#> [97] 0.632559178 0.650654355 0.941822497 0.300584841 0.431087330 0.933448055
#> [103] 0.891341064 0.022342097 0.495809259 0.806755627 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000
#>
#> $Time
#> 79 101 85 169 14 56 49 181 166 155 57 69 194
#> 16.23 9.97 16.44 22.41 12.89 12.21 12.19 16.46 19.98 13.08 14.46 23.23 22.40
#> 63 111 81 105 26 88 145 90 86 108 86.1 149 5
#> 22.77 17.45 14.06 19.75 15.77 18.37 10.07 20.94 23.81 18.29 23.81 8.37 16.43
#> 117 42 190 108.1 111.1 184 8 32 18 88.1 51 39 150
#> 17.46 12.43 20.81 18.29 17.45 17.77 18.43 20.90 15.21 18.37 18.23 15.59 20.33
#> 170 106 125 155.1 24 105.1 15 77 60 117.1 58 76 61
#> 19.54 16.67 15.65 13.08 23.89 19.75 22.68 7.27 13.15 17.46 19.34 19.22 10.12
#> 97 92 79.1 192 51.1 79.2 81.1 194.1 125.1 105.2 69.1 63.1 26.1
#> 19.14 22.92 16.23 16.44 18.23 16.23 14.06 22.40 15.65 19.75 23.23 22.77 15.77
#> 136 30 197 85.1 177 175 129 69.2 164 111.2 90.1 188 110
#> 21.83 17.43 21.60 16.44 12.53 21.91 23.41 23.23 23.60 17.45 20.94 16.16 17.56
#> 107 166.1 66 139 113 18.1 69.3 175.1 26.2 150.1 81.2 39.1 168
#> 11.18 19.98 22.13 21.49 22.86 15.21 23.23 21.91 15.77 20.33 14.06 15.59 23.72
#> 70 175.2 40 169.1 88.2 130 85.2 10 90.2 76.1 159 42.1 78
#> 7.38 21.91 18.00 22.41 18.37 16.47 16.44 10.53 20.94 19.22 10.55 12.43 23.88
#> 108.2 157 98 74 138 64 28 148 38 174 118 121 46
#> 18.29 15.10 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 161 200 54 28.1 64.1 176 80 72 121.1 48 162 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 95 138.1 132 152 47.1 186 74.1 22 112 102 137 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 174.1 75 38.1 161.1 1 21 17 137.1 148.1 119 138.2 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 82.1 48.1 75.1 143 160 35 22.1 53 103 12 176.1 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 3 48.2 148.2 21.1 87 87.1 121.2 191 196 62 33 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 165 21.2 9 104 20 44.1 44.2 148.3 65 72.1 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[19]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0007476429 0.9297828875 0.3151152071
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.459160523 0.009330532 -0.019733782
#> grade_iii, Cure model
#> 0.754983315
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 41 18.02 1 40 1 0
#> 194 22.40 1 38 0 1
#> 13 14.34 1 54 0 1
#> 79 16.23 1 54 1 0
#> 139 21.49 1 63 1 0
#> 180 14.82 1 37 0 0
#> 106 16.67 1 49 1 0
#> 60 13.15 1 38 1 0
#> 187 9.92 1 39 1 0
#> 177 12.53 1 75 0 0
#> 199 19.81 1 NA 0 1
#> 93 10.33 1 52 0 1
#> 190 20.81 1 42 1 0
#> 133 14.65 1 57 0 0
#> 66 22.13 1 53 0 0
#> 180.1 14.82 1 37 0 0
#> 134 17.81 1 47 1 0
#> 4 17.64 1 NA 0 1
#> 136 21.83 1 43 0 1
#> 169 22.41 1 46 0 0
#> 8 18.43 1 32 0 0
#> 23 16.92 1 61 0 0
#> 25 6.32 1 34 1 0
#> 99 21.19 1 38 0 1
#> 15 22.68 1 48 0 0
#> 136.1 21.83 1 43 0 1
#> 100 16.07 1 60 0 0
#> 168 23.72 1 70 0 0
#> 6 15.64 1 39 0 0
#> 168.1 23.72 1 70 0 0
#> 189 10.51 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 171 16.57 1 41 0 1
#> 101 9.97 1 10 0 1
#> 125 15.65 1 67 1 0
#> 45 17.42 1 54 0 1
#> 51 18.23 1 83 0 1
#> 130 16.47 1 53 0 1
#> 167 15.55 1 56 1 0
#> 91 5.33 1 61 0 1
#> 189.1 10.51 1 NA 1 0
#> 101.1 9.97 1 10 0 1
#> 43 12.10 1 61 0 1
#> 199.1 19.81 1 NA 0 1
#> 37 12.52 1 57 1 0
#> 106.1 16.67 1 49 1 0
#> 32 20.90 1 37 1 0
#> 58 19.34 1 39 0 0
#> 36 21.19 1 48 0 1
#> 189.2 10.51 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 77 7.27 1 67 0 1
#> 183 9.24 1 67 1 0
#> 25.1 6.32 1 34 1 0
#> 56 12.21 1 60 0 0
#> 179 18.63 1 42 0 0
#> 88 18.37 1 47 0 0
#> 164 23.60 1 76 0 1
#> 69 23.23 1 25 0 1
#> 32.1 20.90 1 37 1 0
#> 96 14.54 1 33 0 1
#> 181 16.46 1 45 0 1
#> 124 9.73 1 NA 1 0
#> 36.1 21.19 1 48 0 1
#> 184 17.77 1 38 0 0
#> 10 10.53 1 34 0 0
#> 125.1 15.65 1 67 1 0
#> 170 19.54 1 43 0 1
#> 8.1 18.43 1 32 0 0
#> 145 10.07 1 65 1 0
#> 36.2 21.19 1 48 0 1
#> 197 21.60 1 69 1 0
#> 69.1 23.23 1 25 0 1
#> 133.1 14.65 1 57 0 0
#> 190.1 20.81 1 42 1 0
#> 175 21.91 1 43 0 0
#> 24 23.89 1 38 0 0
#> 29 15.45 1 68 1 0
#> 175.1 21.91 1 43 0 0
#> 96.1 14.54 1 33 0 1
#> 101.2 9.97 1 10 0 1
#> 88.1 18.37 1 47 0 0
#> 51.1 18.23 1 83 0 1
#> 194.1 22.40 1 38 0 1
#> 60.1 13.15 1 38 1 0
#> 81 14.06 1 34 0 0
#> 117 17.46 1 26 0 1
#> 108 18.29 1 39 0 1
#> 157 15.10 1 47 0 0
#> 8.2 18.43 1 32 0 0
#> 79.1 16.23 1 54 1 0
#> 60.2 13.15 1 38 1 0
#> 175.2 21.91 1 43 0 0
#> 188 16.16 1 46 0 1
#> 30 17.43 1 78 0 0
#> 91.1 5.33 1 61 0 1
#> 56.1 12.21 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 70 7.38 1 30 1 0
#> 97 19.14 1 65 0 1
#> 145.1 10.07 1 65 1 0
#> 134.1 17.81 1 47 1 0
#> 183.1 9.24 1 67 1 0
#> 41.1 18.02 1 40 1 0
#> 111 17.45 1 47 0 1
#> 15.1 22.68 1 48 0 0
#> 50 10.02 1 NA 1 0
#> 134.2 17.81 1 47 1 0
#> 170.1 19.54 1 43 0 1
#> 108.1 18.29 1 39 0 1
#> 29.1 15.45 1 68 1 0
#> 136.2 21.83 1 43 0 1
#> 121 24.00 0 57 1 0
#> 122 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 83 24.00 0 6 0 0
#> 12 24.00 0 63 0 0
#> 152 24.00 0 36 0 1
#> 28 24.00 0 67 1 0
#> 46 24.00 0 71 0 0
#> 122.1 24.00 0 66 0 0
#> 161.1 24.00 0 45 0 0
#> 62 24.00 0 71 0 0
#> 11 24.00 0 42 0 1
#> 102 24.00 0 49 0 0
#> 116 24.00 0 58 0 1
#> 193 24.00 0 45 0 1
#> 126 24.00 0 48 0 0
#> 160 24.00 0 31 1 0
#> 126.1 24.00 0 48 0 0
#> 28.1 24.00 0 67 1 0
#> 28.2 24.00 0 67 1 0
#> 119 24.00 0 17 0 0
#> 33 24.00 0 53 0 0
#> 147 24.00 0 76 1 0
#> 11.1 24.00 0 42 0 1
#> 176 24.00 0 43 0 1
#> 119.1 24.00 0 17 0 0
#> 138 24.00 0 44 1 0
#> 119.2 24.00 0 17 0 0
#> 44 24.00 0 56 0 0
#> 174 24.00 0 49 1 0
#> 186 24.00 0 45 1 0
#> 109 24.00 0 48 0 0
#> 178 24.00 0 52 1 0
#> 84 24.00 0 39 0 1
#> 137 24.00 0 45 1 0
#> 185 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 34 24.00 0 36 0 0
#> 46.1 24.00 0 71 0 0
#> 20 24.00 0 46 1 0
#> 109.1 24.00 0 48 0 0
#> 83.1 24.00 0 6 0 0
#> 186.1 24.00 0 45 1 0
#> 9 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 47.1 24.00 0 38 0 1
#> 47.2 24.00 0 38 0 1
#> 74 24.00 0 43 0 1
#> 75 24.00 0 21 1 0
#> 84.1 24.00 0 39 0 1
#> 19 24.00 0 57 0 1
#> 75.1 24.00 0 21 1 0
#> 186.2 24.00 0 45 1 0
#> 94 24.00 0 51 0 1
#> 120 24.00 0 68 0 1
#> 44.1 24.00 0 56 0 0
#> 33.1 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 1 24.00 0 23 1 0
#> 11.2 24.00 0 42 0 1
#> 104 24.00 0 50 1 0
#> 160.1 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 112 24.00 0 61 0 0
#> 115 24.00 0 NA 1 0
#> 165 24.00 0 47 0 0
#> 82 24.00 0 34 0 0
#> 98 24.00 0 34 1 0
#> 142 24.00 0 53 0 0
#> 151 24.00 0 42 0 0
#> 142.1 24.00 0 53 0 0
#> 44.2 24.00 0 56 0 0
#> 21 24.00 0 47 0 0
#> 2 24.00 0 9 0 0
#> 146 24.00 0 63 1 0
#> 156 24.00 0 50 1 0
#> 48.1 24.00 0 31 1 0
#> 48.2 24.00 0 31 1 0
#> 178.2 24.00 0 52 1 0
#> 73 24.00 0 NA 0 1
#> 198 24.00 0 66 0 1
#> 102.1 24.00 0 49 0 0
#> 196 24.00 0 19 0 0
#> 104.1 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 151.1 24.00 0 42 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.459 NA NA NA
#> 2 age, Cure model 0.00933 NA NA NA
#> 3 grade_ii, Cure model -0.0197 NA NA NA
#> 4 grade_iii, Cure model 0.755 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000748 NA NA NA
#> 2 grade_ii, Survival model 0.930 NA NA NA
#> 3 grade_iii, Survival model 0.315 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.459161 0.009331 -0.019734 0.754983
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 254.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.459160523 0.009330532 -0.019733782 0.754983315
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0007476429 0.9297828875 0.3151152071
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.55769121 0.18065252 0.81958442 0.69320643 0.32158761 0.77622839
#> [7] 0.65256110 0.83400708 0.94287949 0.86162701 0.90287245 0.40115816
#> [13] 0.79070212 0.20977164 0.77622839 0.57594164 0.26764357 0.16456110
#> [19] 0.47047672 0.64406471 0.97509637 0.33417053 0.13404961 0.26764357
#> [25] 0.71657999 0.05073880 0.73945578 0.05073880 0.03030524 0.66883581
#> [31] 0.92307306 0.72438511 0.63557333 0.53852566 0.67699044 0.74703213
#> [37] 0.98757246 0.92307306 0.88915055 0.86857794 0.65256110 0.37964342
#> [43] 0.44076839 0.33417053 0.85467913 0.96871785 0.94946060 0.97509637
#> [49] 0.87545032 0.46059175 0.49955590 0.08543407 0.10380969 0.37964342
#> [55] 0.80518691 0.68511403 0.33417053 0.60136570 0.89601084 0.72438511
#> [61] 0.42111547 0.47047672 0.90971751 0.33417053 0.30826608 0.10380969
#> [67] 0.79070212 0.40115816 0.22491773 0.01083198 0.75450018 0.22491773
#> [73] 0.80518691 0.92307306 0.49955590 0.53852566 0.18065252 0.83400708
#> [79] 0.82679496 0.60996615 0.51916176 0.76896120 0.47047672 0.69320643
#> [85] 0.83400708 0.22491773 0.70877859 0.62704592 0.98757246 0.87545032
#> [91] 0.96232657 0.45071335 0.90971751 0.57594164 0.94946060 0.55769121
#> [97] 0.61852508 0.13404961 0.57594164 0.42111547 0.51916176 0.75450018
#> [103] 0.26764357 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 41 194 13 79 139 180 106 60 187 177 93 190 133
#> 18.02 22.40 14.34 16.23 21.49 14.82 16.67 13.15 9.92 12.53 10.33 20.81 14.65
#> 66 180.1 134 136 169 8 23 25 99 15 136.1 100 168
#> 22.13 14.82 17.81 21.83 22.41 18.43 16.92 6.32 21.19 22.68 21.83 16.07 23.72
#> 6 168.1 78 171 101 125 45 51 130 167 91 101.1 43
#> 15.64 23.72 23.88 16.57 9.97 15.65 17.42 18.23 16.47 15.55 5.33 9.97 12.10
#> 37 106.1 32 58 36 14 77 183 25.1 56 179 88 164
#> 12.52 16.67 20.90 19.34 21.19 12.89 7.27 9.24 6.32 12.21 18.63 18.37 23.60
#> 69 32.1 96 181 36.1 184 10 125.1 170 8.1 145 36.2 197
#> 23.23 20.90 14.54 16.46 21.19 17.77 10.53 15.65 19.54 18.43 10.07 21.19 21.60
#> 69.1 133.1 190.1 175 24 29 175.1 96.1 101.2 88.1 51.1 194.1 60.1
#> 23.23 14.65 20.81 21.91 23.89 15.45 21.91 14.54 9.97 18.37 18.23 22.40 13.15
#> 81 117 108 157 8.2 79.1 60.2 175.2 188 30 91.1 56.1 70
#> 14.06 17.46 18.29 15.10 18.43 16.23 13.15 21.91 16.16 17.43 5.33 12.21 7.38
#> 97 145.1 134.1 183.1 41.1 111 15.1 134.2 170.1 108.1 29.1 136.2 121
#> 19.14 10.07 17.81 9.24 18.02 17.45 22.68 17.81 19.54 18.29 15.45 21.83 24.00
#> 122 161 83 12 152 28 46 122.1 161.1 62 11 102 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 126 160 126.1 28.1 28.2 119 33 147 11.1 176 119.1 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.2 44 174 186 109 178 84 137 185 47 34 46.1 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.1 83.1 186.1 9 48 178.1 47.1 47.2 74 75 84.1 19 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.2 94 120 44.1 33.1 95 1 11.2 104 160.1 7 112 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 98 142 151 142.1 44.2 21 2 146 156 48.1 48.2 178.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 102.1 196 104.1 65 148 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[20]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005254214 0.936620346 0.217347946
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.329175184 0.000123211 0.323519800
#> grade_iii, Cure model
#> 1.239380635
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 5 16.43 1 51 0 1
#> 181 16.46 1 45 0 1
#> 10 10.53 1 34 0 0
#> 76 19.22 1 54 0 1
#> 51 18.23 1 83 0 1
#> 180 14.82 1 37 0 0
#> 195 11.76 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 192 16.44 1 31 1 0
#> 70 7.38 1 30 1 0
#> 149 8.37 1 33 1 0
#> 92 22.92 1 47 0 1
#> 10.1 10.53 1 34 0 0
#> 45 17.42 1 54 0 1
#> 145 10.07 1 65 1 0
#> 78 23.88 1 43 0 0
#> 86 23.81 1 58 0 1
#> 124 9.73 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 154 12.63 1 20 1 0
#> 175 21.91 1 43 0 0
#> 18 15.21 1 49 1 0
#> 113 22.86 1 34 0 0
#> 100 16.07 1 60 0 0
#> 171 16.57 1 41 0 1
#> 43 12.10 1 61 0 1
#> 70.1 7.38 1 30 1 0
#> 57 14.46 1 45 0 1
#> 123 13.00 1 44 1 0
#> 139 21.49 1 63 1 0
#> 15 22.68 1 48 0 0
#> 88 18.37 1 47 0 0
#> 188 16.16 1 46 0 1
#> 70.2 7.38 1 30 1 0
#> 110 17.56 1 65 0 1
#> 92.1 22.92 1 47 0 1
#> 24 23.89 1 38 0 0
#> 177 12.53 1 75 0 0
#> 113.1 22.86 1 34 0 0
#> 61 10.12 1 36 0 1
#> 113.2 22.86 1 34 0 0
#> 181.1 16.46 1 45 0 1
#> 114 13.68 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 111 17.45 1 47 0 1
#> 181.2 16.46 1 45 0 1
#> 77 7.27 1 67 0 1
#> 149.1 8.37 1 33 1 0
#> 14 12.89 1 21 0 0
#> 32 20.90 1 37 1 0
#> 77.1 7.27 1 67 0 1
#> 29 15.45 1 68 1 0
#> 169 22.41 1 46 0 0
#> 199 19.81 1 NA 0 1
#> 69 23.23 1 25 0 1
#> 8 18.43 1 32 0 0
#> 36 21.19 1 48 0 1
#> 50 10.02 1 NA 1 0
#> 181.3 16.46 1 45 0 1
#> 76.1 19.22 1 54 0 1
#> 114.1 13.68 1 NA 0 0
#> 18.1 15.21 1 49 1 0
#> 56 12.21 1 60 0 0
#> 110.1 17.56 1 65 0 1
#> 184 17.77 1 38 0 0
#> 105 19.75 1 60 0 0
#> 8.1 18.43 1 32 0 0
#> 136 21.83 1 43 0 1
#> 60 13.15 1 38 1 0
#> 58 19.34 1 39 0 0
#> 25 6.32 1 34 1 0
#> 30 17.43 1 78 0 0
#> 189 10.51 1 NA 1 0
#> 139.1 21.49 1 63 1 0
#> 114.2 13.68 1 NA 0 0
#> 134 17.81 1 47 1 0
#> 125 15.65 1 67 1 0
#> 195.1 11.76 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 111.1 17.45 1 47 0 1
#> 194 22.40 1 38 0 1
#> 136.1 21.83 1 43 0 1
#> 179 18.63 1 42 0 0
#> 150 20.33 1 48 0 0
#> 99 21.19 1 38 0 1
#> 153 21.33 1 55 1 0
#> 66 22.13 1 53 0 0
#> 77.2 7.27 1 67 0 1
#> 49 12.19 1 48 1 0
#> 134.1 17.81 1 47 1 0
#> 61.1 10.12 1 36 0 1
#> 107 11.18 1 54 1 0
#> 113.3 22.86 1 34 0 0
#> 189.1 10.51 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 99.1 21.19 1 38 0 1
#> 5.1 16.43 1 51 0 1
#> 58.1 19.34 1 39 0 0
#> 13 14.34 1 54 0 1
#> 136.2 21.83 1 43 0 1
#> 189.2 10.51 1 NA 1 0
#> 10.2 10.53 1 34 0 0
#> 13.1 14.34 1 54 0 1
#> 56.1 12.21 1 60 0 0
#> 55 19.34 1 69 0 1
#> 4 17.64 1 NA 0 1
#> 124.1 9.73 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 166 19.98 1 48 0 0
#> 166.1 19.98 1 48 0 0
#> 57.1 14.46 1 45 0 1
#> 18.2 15.21 1 49 1 0
#> 191 24.00 0 60 0 1
#> 9 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 198 24.00 0 66 0 1
#> 185 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 7 24.00 0 37 1 0
#> 112 24.00 0 61 0 0
#> 94 24.00 0 51 0 1
#> 54 24.00 0 53 1 0
#> 137 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 12 24.00 0 63 0 0
#> 143 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 87 24.00 0 27 0 0
#> 46 24.00 0 71 0 0
#> 112.1 24.00 0 61 0 0
#> 160 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 198.1 24.00 0 66 0 1
#> 161 24.00 0 45 0 0
#> 196 24.00 0 19 0 0
#> 94.1 24.00 0 51 0 1
#> 172 24.00 0 41 0 0
#> 163 24.00 0 66 0 0
#> 17 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 3 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 19 24.00 0 57 0 1
#> 132.1 24.00 0 55 0 0
#> 102 24.00 0 49 0 0
#> 151 24.00 0 42 0 0
#> 27.1 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 20 24.00 0 46 1 0
#> 122 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 82.1 24.00 0 34 0 0
#> 178 24.00 0 52 1 0
#> 80 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 102.1 24.00 0 49 0 0
#> 173 24.00 0 19 0 1
#> 2 24.00 0 9 0 0
#> 80.1 24.00 0 41 0 0
#> 46.1 24.00 0 71 0 0
#> 193 24.00 0 45 0 1
#> 121 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 172.1 24.00 0 41 0 0
#> 80.2 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 75 24.00 0 21 1 0
#> 82.2 24.00 0 34 0 0
#> 44 24.00 0 56 0 0
#> 12.1 24.00 0 63 0 0
#> 44.1 24.00 0 56 0 0
#> 162 24.00 0 51 0 0
#> 119.1 24.00 0 17 0 0
#> 118 24.00 0 44 1 0
#> 172.2 24.00 0 41 0 0
#> 22.1 24.00 0 52 1 0
#> 35.1 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 67 24.00 0 25 0 0
#> 80.3 24.00 0 41 0 0
#> 156 24.00 0 50 1 0
#> 141 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 54.1 24.00 0 53 1 0
#> 83.1 24.00 0 6 0 0
#> 46.2 24.00 0 71 0 0
#> 116 24.00 0 58 0 1
#> 17.1 24.00 0 38 0 1
#> 121.1 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 122.1 24.00 0 66 0 0
#> 119.2 24.00 0 17 0 0
#> 143.1 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 147 24.00 0 76 1 0
#> 9.1 24.00 0 31 1 0
#> 87.1 24.00 0 27 0 0
#> 80.4 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.329 NA NA NA
#> 2 age, Cure model 0.000123 NA NA NA
#> 3 grade_ii, Cure model 0.324 NA NA NA
#> 4 grade_iii, Cure model 1.24 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00525 NA NA NA
#> 2 grade_ii, Survival model 0.937 NA NA NA
#> 3 grade_iii, Survival model 0.217 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.3291752 0.0001232 0.3235198 1.2393806
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.6
#> Residual Deviance: 246.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.329175184 0.000123211 0.323519800 1.239380635
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005254214 0.936620346 0.217347946
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.74584019 0.70053687 0.91655689 0.54507052 0.60125252 0.82296328
#> [7] 0.78256930 0.73086339 0.96260244 0.95142798 0.14838807 0.91655689
#> [13] 0.68467224 0.94568666 0.06510638 0.09752886 0.73086339 0.87419419
#> [19] 0.31819191 0.79673980 0.18645060 0.76802135 0.69262915 0.90467861
#> [25] 0.96260244 0.82953659 0.86170884 0.37721539 0.25052440 0.59191462
#> [31] 0.76063146 0.96260244 0.64434999 0.14838807 0.02870334 0.88035361
#> [37] 0.18645060 0.93405656 0.18645060 0.70053687 0.44524021 0.66061902
#> [43] 0.70053687 0.97875808 0.95142798 0.86795413 0.45606528 0.97875808
#> [49] 0.78973867 0.26800216 0.12403097 0.57330455 0.41307825 0.70053687
#> [55] 0.54507052 0.79673980 0.88649229 0.64434999 0.63600472 0.50654482
#> [61] 0.57330455 0.33434557 0.85536166 0.51648607 0.99471172 0.67665473
#> [67] 0.37721539 0.61937579 0.77538497 0.81637869 0.66061902 0.28517424
#> [73] 0.33434557 0.56386622 0.47657677 0.41307825 0.40156567 0.30182789
#> [79] 0.97875808 0.89866487 0.61937579 0.93405656 0.91066400 0.18645060
#> [85] 0.61045858 0.41307825 0.74584019 0.51648607 0.84251348 0.33434557
#> [91] 0.91655689 0.84251348 0.88649229 0.51648607 0.46637668 0.48671463
#> [97] 0.48671463 0.82953659 0.79673980 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 5 181 10 76 51 180 6 192 70 149 92 10.1 45
#> 16.43 16.46 10.53 19.22 18.23 14.82 15.64 16.44 7.38 8.37 22.92 10.53 17.42
#> 145 78 86 85 154 175 18 113 100 171 43 70.1 57
#> 10.07 23.88 23.81 16.44 12.63 21.91 15.21 22.86 16.07 16.57 12.10 7.38 14.46
#> 123 139 15 88 188 70.2 110 92.1 24 177 113.1 61 113.2
#> 13.00 21.49 22.68 18.37 16.16 7.38 17.56 22.92 23.89 12.53 22.86 10.12 22.86
#> 181.1 90 111 181.2 77 149.1 14 32 77.1 29 169 69 8
#> 16.46 20.94 17.45 16.46 7.27 8.37 12.89 20.90 7.27 15.45 22.41 23.23 18.43
#> 36 181.3 76.1 18.1 56 110.1 184 105 8.1 136 60 58 25
#> 21.19 16.46 19.22 15.21 12.21 17.56 17.77 19.75 18.43 21.83 13.15 19.34 6.32
#> 30 139.1 134 125 157 111.1 194 136.1 179 150 99 153 66
#> 17.43 21.49 17.81 15.65 15.10 17.45 22.40 21.83 18.63 20.33 21.19 21.33 22.13
#> 77.2 49 134.1 61.1 107 113.3 41 99.1 5.1 58.1 13 136.2 10.2
#> 7.27 12.19 17.81 10.12 11.18 22.86 18.02 21.19 16.43 19.34 14.34 21.83 10.53
#> 13.1 56.1 55 128 166 166.1 57.1 18.2 191 9 120 83 198
#> 14.34 12.21 19.34 20.35 19.98 19.98 14.46 15.21 24.00 24.00 24.00 24.00 24.00
#> 185 132 7 112 94 54 137 27 12 143 22 109 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 112.1 160 47 198.1 161 196 94.1 172 163 17 82 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 19 132.1 102 151 27.1 119 20 122 174 82.1 178 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 102.1 173 2 80.1 46.1 193 121 35 172.1 80.2 72 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.2 44 12.1 44.1 162 119.1 118 172.2 22.1 35.1 31 67 80.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 141 186 54.1 83.1 46.2 116 17.1 121.1 138 122.1 119.2 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 147 9.1 87.1 80.4
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[21]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01800658 0.41272325 1.04122943
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.94392165 0.01077687 0.79016880
#> grade_iii, Cure model
#> 0.90572625
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 124 9.73 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 184 17.77 1 38 0 0
#> 25 6.32 1 34 1 0
#> 40 18.00 1 28 1 0
#> 157 15.10 1 47 0 0
#> 127 3.53 1 62 0 1
#> 49 12.19 1 48 1 0
#> 70 7.38 1 30 1 0
#> 153 21.33 1 55 1 0
#> 159 10.55 1 50 0 1
#> 108 18.29 1 39 0 1
#> 129 23.41 1 53 1 0
#> 70.1 7.38 1 30 1 0
#> 42 12.43 1 49 0 1
#> 77 7.27 1 67 0 1
#> 124.1 9.73 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 76 19.22 1 54 0 1
#> 164 23.60 1 76 0 1
#> 123 13.00 1 44 1 0
#> 153.1 21.33 1 55 1 0
#> 169 22.41 1 46 0 0
#> 93 10.33 1 52 0 1
#> 79 16.23 1 54 1 0
#> 100 16.07 1 60 0 0
#> 175 21.91 1 43 0 0
#> 129.1 23.41 1 53 1 0
#> 57 14.46 1 45 0 1
#> 45 17.42 1 54 0 1
#> 81 14.06 1 34 0 0
#> 127.1 3.53 1 62 0 1
#> 168 23.72 1 70 0 0
#> 39 15.59 1 37 0 1
#> 125 15.65 1 67 1 0
#> 106 16.67 1 49 1 0
#> 187 9.92 1 39 1 0
#> 89 11.44 1 NA 0 0
#> 107 11.18 1 54 1 0
#> 52 10.42 1 52 0 1
#> 63 22.77 1 31 1 0
#> 52.1 10.42 1 52 0 1
#> 50 10.02 1 NA 1 0
#> 25.1 6.32 1 34 1 0
#> 42.1 12.43 1 49 0 1
#> 78 23.88 1 43 0 0
#> 199 19.81 1 NA 0 1
#> 76.1 19.22 1 54 0 1
#> 129.2 23.41 1 53 1 0
#> 123.1 13.00 1 44 1 0
#> 129.3 23.41 1 53 1 0
#> 111 17.45 1 47 0 1
#> 89.1 11.44 1 NA 0 0
#> 114 13.68 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 197 21.60 1 69 1 0
#> 169.1 22.41 1 46 0 0
#> 16 8.71 1 71 0 1
#> 16.1 8.71 1 71 0 1
#> 41 18.02 1 40 1 0
#> 26 15.77 1 49 0 1
#> 130 16.47 1 53 0 1
#> 40.1 18.00 1 28 1 0
#> 157.1 15.10 1 47 0 0
#> 45.1 17.42 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 154 12.63 1 20 1 0
#> 8 18.43 1 32 0 0
#> 167 15.55 1 56 1 0
#> 139 21.49 1 63 1 0
#> 167.1 15.55 1 56 1 0
#> 96 14.54 1 33 0 1
#> 40.2 18.00 1 28 1 0
#> 129.4 23.41 1 53 1 0
#> 89.2 11.44 1 NA 0 0
#> 41.1 18.02 1 40 1 0
#> 127.2 3.53 1 62 0 1
#> 110 17.56 1 65 0 1
#> 37 12.52 1 57 1 0
#> 58 19.34 1 39 0 0
#> 4.1 17.64 1 NA 0 1
#> 96.1 14.54 1 33 0 1
#> 40.3 18.00 1 28 1 0
#> 86 23.81 1 58 0 1
#> 60 13.15 1 38 1 0
#> 32 20.90 1 37 1 0
#> 140.1 12.68 1 59 1 0
#> 159.1 10.55 1 50 0 1
#> 169.2 22.41 1 46 0 0
#> 15 22.68 1 48 0 0
#> 114.1 13.68 1 NA 0 0
#> 32.1 20.90 1 37 1 0
#> 129.5 23.41 1 53 1 0
#> 66.1 22.13 1 53 0 0
#> 153.2 21.33 1 55 1 0
#> 70.2 7.38 1 30 1 0
#> 133 14.65 1 57 0 0
#> 188 16.16 1 46 0 1
#> 96.2 14.54 1 33 0 1
#> 85 16.44 1 36 0 0
#> 29 15.45 1 68 1 0
#> 32.2 20.90 1 37 1 0
#> 169.3 22.41 1 46 0 0
#> 30 17.43 1 78 0 0
#> 155 13.08 1 26 0 0
#> 79.1 16.23 1 54 1 0
#> 4.2 17.64 1 NA 0 1
#> 91 5.33 1 61 0 1
#> 101 9.97 1 10 0 1
#> 125.1 15.65 1 67 1 0
#> 145 10.07 1 65 1 0
#> 68 20.62 1 44 0 0
#> 11 24.00 0 42 0 1
#> 83 24.00 0 6 0 0
#> 35 24.00 0 51 0 0
#> 33 24.00 0 53 0 0
#> 7 24.00 0 37 1 0
#> 62 24.00 0 71 0 0
#> 75 24.00 0 21 1 0
#> 11.1 24.00 0 42 0 1
#> 163 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 12 24.00 0 63 0 0
#> 191 24.00 0 60 0 1
#> 165 24.00 0 47 0 0
#> 82 24.00 0 34 0 0
#> 2 24.00 0 9 0 0
#> 84 24.00 0 39 0 1
#> 73 24.00 0 NA 0 1
#> 200 24.00 0 64 0 0
#> 160 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 120 24.00 0 68 0 1
#> 109 24.00 0 48 0 0
#> 87 24.00 0 27 0 0
#> 115 24.00 0 NA 1 0
#> 104 24.00 0 50 1 0
#> 19.1 24.00 0 57 0 1
#> 186 24.00 0 45 1 0
#> 7.1 24.00 0 37 1 0
#> 31 24.00 0 36 0 1
#> 137 24.00 0 45 1 0
#> 143.1 24.00 0 51 0 0
#> 31.1 24.00 0 36 0 1
#> 193 24.00 0 45 0 1
#> 75.1 24.00 0 21 1 0
#> 3 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 11.2 24.00 0 42 0 1
#> 120.1 24.00 0 68 0 1
#> 19.2 24.00 0 57 0 1
#> 161 24.00 0 45 0 0
#> 65 24.00 0 57 1 0
#> 38 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 3.1 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 71 24.00 0 51 0 0
#> 19.3 24.00 0 57 0 1
#> 53 24.00 0 32 0 1
#> 64 24.00 0 43 0 0
#> 2.1 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 122 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 104.1 24.00 0 50 1 0
#> 103.1 24.00 0 56 1 0
#> 122.1 24.00 0 66 0 0
#> 35.1 24.00 0 51 0 0
#> 31.2 24.00 0 36 0 1
#> 200.1 24.00 0 64 0 0
#> 161.1 24.00 0 45 0 0
#> 126 24.00 0 48 0 0
#> 142 24.00 0 53 0 0
#> 112 24.00 0 61 0 0
#> 7.2 24.00 0 37 1 0
#> 162 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 178 24.00 0 52 1 0
#> 196 24.00 0 19 0 0
#> 11.3 24.00 0 42 0 1
#> 174.1 24.00 0 49 1 0
#> 186.1 24.00 0 45 1 0
#> 94 24.00 0 51 0 1
#> 27 24.00 0 63 1 0
#> 138 24.00 0 44 1 0
#> 62.1 24.00 0 71 0 0
#> 17 24.00 0 38 0 1
#> 103.2 24.00 0 56 1 0
#> 118 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 38.1 24.00 0 31 1 0
#> 193.1 24.00 0 45 0 1
#> 9 24.00 0 31 1 0
#> 143.2 24.00 0 51 0 0
#> 7.3 24.00 0 37 1 0
#> 147 24.00 0 76 1 0
#> 103.3 24.00 0 56 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.944 NA NA NA
#> 2 age, Cure model 0.0108 NA NA NA
#> 3 grade_ii, Cure model 0.790 NA NA NA
#> 4 grade_iii, Cure model 0.906 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0180 NA NA NA
#> 2 grade_ii, Survival model 0.413 NA NA NA
#> 3 grade_iii, Survival model 1.04 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.94392 0.01078 0.79017 0.90573
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 248.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.94392165 0.01077687 0.79016880 0.90572625
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01800658 0.41272325 1.04122943
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6344841732 0.2671468143 0.9239517816 0.2281205732 0.4895362615
#> [6] 0.9620797274 0.7096852972 0.8737501141 0.0962704236 0.7478644842
#> [11] 0.1979728536 0.0104107447 0.8737501141 0.6846998280 0.9112495626
#> [16] 0.7223718510 0.1682270465 0.0069359214 0.6099981350 0.0962704236
#> [21] 0.0379219942 0.7982518789 0.3633908893 0.3968096314 0.0726499215
#> [26] 0.0104107447 0.5616617673 0.3095897033 0.5736067994 0.9620797274
#> [31] 0.0039058160 0.4426552309 0.4195757831 0.3307032292 0.8361568189
#> [36] 0.7350708033 0.7731035366 0.0285231211 0.7731035366 0.9239517816
#> [41] 0.6846998280 0.0002248113 0.1682270465 0.0104107447 0.6099981350
#> [46] 0.0104107447 0.2882836534 0.0591843673 0.0801199428 0.0379219942
#> [51] 0.8486979391 0.8486979391 0.2080161910 0.4082200289 0.3415662067
#> [56] 0.2281205732 0.4895362615 0.3095897033 0.6594302426 0.1877197943
#> [61] 0.4542105608 0.0880047056 0.4542105608 0.5263927416 0.2281205732
#> [66] 0.0104107447 0.2080161910 0.9620797274 0.2776908384 0.6720105600
#> [71] 0.1580958040 0.5263927416 0.2281205732 0.0019670649 0.5856668238
#> [76] 0.1216457617 0.6344841732 0.7478644842 0.0379219942 0.0330291897
#> [81] 0.1216457617 0.0104107447 0.0591843673 0.0962704236 0.8737501141
#> [86] 0.5138804669 0.3856119306 0.5263927416 0.3523979479 0.4775536460
#> [91] 0.1216457617 0.0379219942 0.2987934107 0.5977861970 0.3633908893
#> [96] 0.9493068481 0.8236628092 0.4195757831 0.8109044645 0.1482819661
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000
#>
#> $Time
#> 140 184 25 40 157 127 49 70 153 159 108 129 70.1
#> 12.68 17.77 6.32 18.00 15.10 3.53 12.19 7.38 21.33 10.55 18.29 23.41 7.38
#> 42 77 43 76 164 123 153.1 169 93 79 100 175 129.1
#> 12.43 7.27 12.10 19.22 23.60 13.00 21.33 22.41 10.33 16.23 16.07 21.91 23.41
#> 57 45 81 127.1 168 39 125 106 187 107 52 63 52.1
#> 14.46 17.42 14.06 3.53 23.72 15.59 15.65 16.67 9.92 11.18 10.42 22.77 10.42
#> 25.1 42.1 78 76.1 129.2 123.1 129.3 111 66 197 169.1 16 16.1
#> 6.32 12.43 23.88 19.22 23.41 13.00 23.41 17.45 22.13 21.60 22.41 8.71 8.71
#> 41 26 130 40.1 157.1 45.1 154 8 167 139 167.1 96 40.2
#> 18.02 15.77 16.47 18.00 15.10 17.42 12.63 18.43 15.55 21.49 15.55 14.54 18.00
#> 129.4 41.1 127.2 110 37 58 96.1 40.3 86 60 32 140.1 159.1
#> 23.41 18.02 3.53 17.56 12.52 19.34 14.54 18.00 23.81 13.15 20.90 12.68 10.55
#> 169.2 15 32.1 129.5 66.1 153.2 70.2 133 188 96.2 85 29 32.2
#> 22.41 22.68 20.90 23.41 22.13 21.33 7.38 14.65 16.16 14.54 16.44 15.45 20.90
#> 169.3 30 155 79.1 91 101 125.1 145 68 11 83 35 33
#> 22.41 17.43 13.08 16.23 5.33 9.97 15.65 10.07 20.62 24.00 24.00 24.00 24.00
#> 7 62 75 11.1 163 103 12 191 165 82 2 84 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 143 19 120 109 87 104 19.1 186 7.1 31 137 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 193 75.1 3 121 11.2 120.1 19.2 161 65 38 146 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 33.1 71 19.3 53 64 2.1 172 122 22 104.1 103.1 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.1 31.2 200.1 161.1 126 142 112 7.2 162 174 178 196 11.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.1 186.1 94 27 138 62.1 17 103.2 118 80 38.1 193.1 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.2 7.3 147 103.3
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[22]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008053544 0.883439390 0.532717765
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.45863526 0.00257302 0.56877456
#> grade_iii, Cure model
#> 0.95484331
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 37 12.52 1 57 1 0
#> 188 16.16 1 46 0 1
#> 18 15.21 1 49 1 0
#> 100 16.07 1 60 0 0
#> 77 7.27 1 67 0 1
#> 49 12.19 1 48 1 0
#> 187 9.92 1 39 1 0
#> 10 10.53 1 34 0 0
#> 164 23.60 1 76 0 1
#> 93 10.33 1 52 0 1
#> 79 16.23 1 54 1 0
#> 124 9.73 1 NA 1 0
#> 189 10.51 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 37.1 12.52 1 57 1 0
#> 101 9.97 1 10 0 1
#> 113 22.86 1 34 0 0
#> 76 19.22 1 54 0 1
#> 40 18.00 1 28 1 0
#> 45 17.42 1 54 0 1
#> 91 5.33 1 61 0 1
#> 181 16.46 1 45 0 1
#> 4 17.64 1 NA 0 1
#> 127.1 3.53 1 62 0 1
#> 32 20.90 1 37 1 0
#> 189.1 10.51 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 157 15.10 1 47 0 0
#> 40.1 18.00 1 28 1 0
#> 51 18.23 1 83 0 1
#> 159 10.55 1 50 0 1
#> 134 17.81 1 47 1 0
#> 192 16.44 1 31 1 0
#> 181.1 16.46 1 45 0 1
#> 190 20.81 1 42 1 0
#> 167 15.55 1 56 1 0
#> 158 20.14 1 74 1 0
#> 110 17.56 1 65 0 1
#> 42 12.43 1 49 0 1
#> 133 14.65 1 57 0 0
#> 169 22.41 1 46 0 0
#> 106 16.67 1 49 1 0
#> 81 14.06 1 34 0 0
#> 14 12.89 1 21 0 0
#> 130 16.47 1 53 0 1
#> 133.1 14.65 1 57 0 0
#> 190.1 20.81 1 42 1 0
#> 86 23.81 1 58 0 1
#> 128 20.35 1 35 0 1
#> 171 16.57 1 41 0 1
#> 113.1 22.86 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 77.1 7.27 1 67 0 1
#> 91.1 5.33 1 61 0 1
#> 154 12.63 1 20 1 0
#> 81.1 14.06 1 34 0 0
#> 177 12.53 1 75 0 0
#> 79.1 16.23 1 54 1 0
#> 14.1 12.89 1 21 0 0
#> 164.1 23.60 1 76 0 1
#> 129 23.41 1 53 1 0
#> 86.1 23.81 1 58 0 1
#> 40.2 18.00 1 28 1 0
#> 93.1 10.33 1 52 0 1
#> 157.1 15.10 1 47 0 0
#> 169.1 22.41 1 46 0 0
#> 125 15.65 1 67 1 0
#> 24 23.89 1 38 0 0
#> 150 20.33 1 48 0 0
#> 107 11.18 1 54 1 0
#> 117 17.46 1 26 0 1
#> 92 22.92 1 47 0 1
#> 134.1 17.81 1 47 1 0
#> 24.1 23.89 1 38 0 0
#> 187.1 9.92 1 39 1 0
#> 197 21.60 1 69 1 0
#> 99 21.19 1 38 0 1
#> 105 19.75 1 60 0 0
#> 25 6.32 1 34 1 0
#> 70 7.38 1 30 1 0
#> 195 11.76 1 NA 1 0
#> 150.1 20.33 1 48 0 0
#> 70.1 7.38 1 30 1 0
#> 50 10.02 1 NA 1 0
#> 50.1 10.02 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 25.1 6.32 1 34 1 0
#> 117.1 17.46 1 26 0 1
#> 51.1 18.23 1 83 0 1
#> 111.1 17.45 1 47 0 1
#> 168 23.72 1 70 0 0
#> 99.1 21.19 1 38 0 1
#> 177.1 12.53 1 75 0 0
#> 86.2 23.81 1 58 0 1
#> 117.2 17.46 1 26 0 1
#> 79.2 16.23 1 54 1 0
#> 51.2 18.23 1 83 0 1
#> 96 14.54 1 33 0 1
#> 24.2 23.89 1 38 0 0
#> 70.2 7.38 1 30 1 0
#> 171.1 16.57 1 41 0 1
#> 51.3 18.23 1 83 0 1
#> 188.1 16.16 1 46 0 1
#> 117.3 17.46 1 26 0 1
#> 89 11.44 1 NA 0 0
#> 105.1 19.75 1 60 0 0
#> 24.3 23.89 1 38 0 0
#> 10.1 10.53 1 34 0 0
#> 154.1 12.63 1 20 1 0
#> 114 13.68 1 NA 0 0
#> 49.1 12.19 1 48 1 0
#> 60 13.15 1 38 1 0
#> 191 24.00 0 60 0 1
#> 173 24.00 0 19 0 1
#> 173.1 24.00 0 19 0 1
#> 102 24.00 0 49 0 0
#> 65 24.00 0 57 1 0
#> 151 24.00 0 42 0 0
#> 144 24.00 0 28 0 1
#> 147 24.00 0 76 1 0
#> 112 24.00 0 61 0 0
#> 142 24.00 0 53 0 0
#> 2 24.00 0 9 0 0
#> 132 24.00 0 55 0 0
#> 178 24.00 0 52 1 0
#> 132.1 24.00 0 55 0 0
#> 147.1 24.00 0 76 1 0
#> 148 24.00 0 61 1 0
#> 116 24.00 0 58 0 1
#> 122 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 2.1 24.00 0 9 0 0
#> 152 24.00 0 36 0 1
#> 186 24.00 0 45 1 0
#> 191.1 24.00 0 60 0 1
#> 138 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 152.1 24.00 0 36 0 1
#> 138.1 24.00 0 44 1 0
#> 147.2 24.00 0 76 1 0
#> 1 24.00 0 23 1 0
#> 2.2 24.00 0 9 0 0
#> 21 24.00 0 47 0 0
#> 198 24.00 0 66 0 1
#> 35 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 9 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 196 24.00 0 19 0 0
#> 31 24.00 0 36 0 1
#> 112.1 24.00 0 61 0 0
#> 161 24.00 0 45 0 0
#> 198.1 24.00 0 66 0 1
#> 165 24.00 0 47 0 0
#> 120 24.00 0 68 0 1
#> 131 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 74 24.00 0 43 0 1
#> 17 24.00 0 38 0 1
#> 182 24.00 0 35 0 0
#> 46 24.00 0 71 0 0
#> 148.1 24.00 0 61 1 0
#> 135 24.00 0 58 1 0
#> 94 24.00 0 51 0 1
#> 146 24.00 0 63 1 0
#> 87 24.00 0 27 0 0
#> 115 24.00 0 NA 1 0
#> 71 24.00 0 51 0 0
#> 146.1 24.00 0 63 1 0
#> 104.1 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 11.1 24.00 0 42 0 1
#> 27 24.00 0 63 1 0
#> 126 24.00 0 48 0 0
#> 38 24.00 0 31 1 0
#> 144.1 24.00 0 28 0 1
#> 119 24.00 0 17 0 0
#> 131.1 24.00 0 66 0 0
#> 151.1 24.00 0 42 0 0
#> 71.1 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 148.2 24.00 0 61 1 0
#> 162 24.00 0 51 0 0
#> 142.1 24.00 0 53 0 0
#> 142.2 24.00 0 53 0 0
#> 131.2 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 138.2 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 71.2 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 38.1 24.00 0 31 1 0
#> 182.1 24.00 0 35 0 0
#> 161.1 24.00 0 45 0 0
#> 131.3 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 75 24.00 0 21 1 0
#> 165.1 24.00 0 47 0 0
#> 53 24.00 0 32 0 1
#> 152.2 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.459 NA NA NA
#> 2 age, Cure model 0.00257 NA NA NA
#> 3 grade_ii, Cure model 0.569 NA NA NA
#> 4 grade_iii, Cure model 0.955 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00805 NA NA NA
#> 2 grade_ii, Survival model 0.883 NA NA NA
#> 3 grade_iii, Survival model 0.533 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.458635 0.002573 0.568775 0.954843
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 253.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.45863526 0.00257302 0.56877456 0.95484331
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008053544 0.883439390 0.532717765
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.79100566 0.61253327 0.65748351 0.63044516 0.93536663 0.81717617
#> [7] 0.89422044 0.85147855 0.09138523 0.86860196 0.58572581 0.98391208
#> [13] 0.79100566 0.88568475 0.13915278 0.33638966 0.39132872 0.50987076
#> [19] 0.96781523 0.55764771 0.98391208 0.23688014 0.18719602 0.66635776
#> [25] 0.39132872 0.34766897 0.84291482 0.42212218 0.57640492 0.55764771
#> [31] 0.24868772 0.64853311 0.30310682 0.44225820 0.80843038 0.68413633
#> [37] 0.16262320 0.51960237 0.71108447 0.73803901 0.54812897 0.68413633
#> [43] 0.24868772 0.04834368 0.27029262 0.52922043 0.13915278 0.93536663
#> [49] 0.96781523 0.75592601 0.71108447 0.77337565 0.58572581 0.73803901
#> [55] 0.09138523 0.11542048 0.04834368 0.39132872 0.86860196 0.66635776
#> [61] 0.16262320 0.63951538 0.01243240 0.28119330 0.83433900 0.45244133
#> [67] 0.12737831 0.42212218 0.01243240 0.89422044 0.20022221 0.21292819
#> [73] 0.31413392 0.95170705 0.91096628 0.28119330 0.91096628 0.49055577
#> [79] 0.95170705 0.45244133 0.34766897 0.49055577 0.07874612 0.21292819
#> [85] 0.77337565 0.04834368 0.45244133 0.58572581 0.34766897 0.70208663
#> [91] 0.01243240 0.91096628 0.52922043 0.34766897 0.61253327 0.45244133
#> [97] 0.31413392 0.01243240 0.85147855 0.75592601 0.81717617 0.72907468
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 37 188 18 100 77 49 187 10 164 93 79 127 37.1
#> 12.52 16.16 15.21 16.07 7.27 12.19 9.92 10.53 23.60 10.33 16.23 3.53 12.52
#> 101 113 76 40 45 91 181 127.1 32 66 157 40.1 51
#> 9.97 22.86 19.22 18.00 17.42 5.33 16.46 3.53 20.90 22.13 15.10 18.00 18.23
#> 159 134 192 181.1 190 167 158 110 42 133 169 106 81
#> 10.55 17.81 16.44 16.46 20.81 15.55 20.14 17.56 12.43 14.65 22.41 16.67 14.06
#> 14 130 133.1 190.1 86 128 171 113.1 77.1 91.1 154 81.1 177
#> 12.89 16.47 14.65 20.81 23.81 20.35 16.57 22.86 7.27 5.33 12.63 14.06 12.53
#> 79.1 14.1 164.1 129 86.1 40.2 93.1 157.1 169.1 125 24 150 107
#> 16.23 12.89 23.60 23.41 23.81 18.00 10.33 15.10 22.41 15.65 23.89 20.33 11.18
#> 117 92 134.1 24.1 187.1 197 99 105 25 70 150.1 70.1 111
#> 17.46 22.92 17.81 23.89 9.92 21.60 21.19 19.75 6.32 7.38 20.33 7.38 17.45
#> 25.1 117.1 51.1 111.1 168 99.1 177.1 86.2 117.2 79.2 51.2 96 24.2
#> 6.32 17.46 18.23 17.45 23.72 21.19 12.53 23.81 17.46 16.23 18.23 14.54 23.89
#> 70.2 171.1 51.3 188.1 117.3 105.1 24.3 10.1 154.1 49.1 60 191 173
#> 7.38 16.57 18.23 16.16 17.46 19.75 23.89 10.53 12.63 12.19 13.15 24.00 24.00
#> 173.1 102 65 151 144 147 112 142 2 132 178 132.1 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 116 122 104 2.1 152 186 191.1 138 82 152.1 138.1 147.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 2.2 21 198 35 95 9 28 196 31 112.1 161 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 120 131 47 74 17 182 46 148.1 135 94 146 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 146.1 104.1 11 11.1 27 126 38 144.1 119 131.1 151.1 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 148.2 162 142.1 142.2 131.2 185 138.2 3 71.2 64 38.1 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 131.3 20 75 165.1 53 152.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[23]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.02266937 0.33285823 0.28467699
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.82803321 0.01016474 0.46646189
#> grade_iii, Cure model
#> 1.23114772
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 63 22.77 1 31 1 0
#> 36 21.19 1 48 0 1
#> 96 14.54 1 33 0 1
#> 149 8.37 1 33 1 0
#> 56 12.21 1 60 0 0
#> 45 17.42 1 54 0 1
#> 183 9.24 1 67 1 0
#> 91 5.33 1 61 0 1
#> 107 11.18 1 54 1 0
#> 153 21.33 1 55 1 0
#> 171 16.57 1 41 0 1
#> 76 19.22 1 54 0 1
#> 26 15.77 1 49 0 1
#> 24 23.89 1 38 0 0
#> 55 19.34 1 69 0 1
#> 81 14.06 1 34 0 0
#> 167 15.55 1 56 1 0
#> 29 15.45 1 68 1 0
#> 125 15.65 1 67 1 0
#> 49 12.19 1 48 1 0
#> 183.1 9.24 1 67 1 0
#> 111 17.45 1 47 0 1
#> 79 16.23 1 54 1 0
#> 157 15.10 1 47 0 0
#> 90 20.94 1 50 0 1
#> 130 16.47 1 53 0 1
#> 24.1 23.89 1 38 0 0
#> 195 11.76 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 5 16.43 1 51 0 1
#> 153.1 21.33 1 55 1 0
#> 194 22.40 1 38 0 1
#> 117 17.46 1 26 0 1
#> 90.1 20.94 1 50 0 1
#> 91.1 5.33 1 61 0 1
#> 106 16.67 1 49 1 0
#> 155 13.08 1 26 0 0
#> 51 18.23 1 83 0 1
#> 59 10.16 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 23 16.92 1 61 0 0
#> 39 15.59 1 37 0 1
#> 140 12.68 1 59 1 0
#> 70 7.38 1 30 1 0
#> 49.1 12.19 1 48 1 0
#> 79.1 16.23 1 54 1 0
#> 177.1 12.53 1 75 0 0
#> 89 11.44 1 NA 0 0
#> 68 20.62 1 44 0 0
#> 57 14.46 1 45 0 1
#> 41 18.02 1 40 1 0
#> 26.1 15.77 1 49 0 1
#> 79.2 16.23 1 54 1 0
#> 117.1 17.46 1 26 0 1
#> 197 21.60 1 69 1 0
#> 166 19.98 1 48 0 0
#> 150 20.33 1 48 0 0
#> 113 22.86 1 34 0 0
#> 76.1 19.22 1 54 0 1
#> 50 10.02 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 136 21.83 1 43 0 1
#> 195.1 11.76 1 NA 1 0
#> 194.1 22.40 1 38 0 1
#> 150.1 20.33 1 48 0 0
#> 76.2 19.22 1 54 0 1
#> 100 16.07 1 60 0 0
#> 57.1 14.46 1 45 0 1
#> 167.1 15.55 1 56 1 0
#> 166.1 19.98 1 48 0 0
#> 88 18.37 1 47 0 0
#> 43 12.10 1 61 0 1
#> 43.1 12.10 1 61 0 1
#> 32 20.90 1 37 1 0
#> 85 16.44 1 36 0 0
#> 85.1 16.44 1 36 0 0
#> 110 17.56 1 65 0 1
#> 145 10.07 1 65 1 0
#> 169 22.41 1 46 0 0
#> 177.2 12.53 1 75 0 0
#> 134.1 17.81 1 47 1 0
#> 8 18.43 1 32 0 0
#> 13 14.34 1 54 0 1
#> 77 7.27 1 67 0 1
#> 134.2 17.81 1 47 1 0
#> 18 15.21 1 49 1 0
#> 179 18.63 1 42 0 0
#> 8.1 18.43 1 32 0 0
#> 51.1 18.23 1 83 0 1
#> 89.1 11.44 1 NA 0 0
#> 63.1 22.77 1 31 1 0
#> 69 23.23 1 25 0 1
#> 150.2 20.33 1 48 0 0
#> 159 10.55 1 50 0 1
#> 88.1 18.37 1 47 0 0
#> 25 6.32 1 34 1 0
#> 97 19.14 1 65 0 1
#> 149.1 8.37 1 33 1 0
#> 153.2 21.33 1 55 1 0
#> 58 19.34 1 39 0 0
#> 49.2 12.19 1 48 1 0
#> 91.2 5.33 1 61 0 1
#> 91.3 5.33 1 61 0 1
#> 171.1 16.57 1 41 0 1
#> 52 10.42 1 52 0 1
#> 158 20.14 1 74 1 0
#> 10 10.53 1 34 0 0
#> 183.2 9.24 1 67 1 0
#> 43.2 12.10 1 61 0 1
#> 190 20.81 1 42 1 0
#> 183.3 9.24 1 67 1 0
#> 189 10.51 1 NA 1 0
#> 176 24.00 0 43 0 1
#> 20 24.00 0 46 1 0
#> 135 24.00 0 58 1 0
#> 71 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 64 24.00 0 43 0 0
#> 20.1 24.00 0 46 1 0
#> 126 24.00 0 48 0 0
#> 104 24.00 0 50 1 0
#> 178.1 24.00 0 52 1 0
#> 198 24.00 0 66 0 1
#> 62 24.00 0 71 0 0
#> 103 24.00 0 56 1 0
#> 161 24.00 0 45 0 0
#> 54 24.00 0 53 1 0
#> 67 24.00 0 25 0 0
#> 137 24.00 0 45 1 0
#> 185 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 67.1 24.00 0 25 0 0
#> 46 24.00 0 71 0 0
#> 80 24.00 0 41 0 0
#> 186 24.00 0 45 1 0
#> 191 24.00 0 60 0 1
#> 54.1 24.00 0 53 1 0
#> 109 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 104.1 24.00 0 50 1 0
#> 141 24.00 0 44 1 0
#> 67.2 24.00 0 25 0 0
#> 65 24.00 0 57 1 0
#> 21 24.00 0 47 0 0
#> 103.1 24.00 0 56 1 0
#> 172 24.00 0 41 0 0
#> 148 24.00 0 61 1 0
#> 120 24.00 0 68 0 1
#> 75 24.00 0 21 1 0
#> 142 24.00 0 53 0 0
#> 7 24.00 0 37 1 0
#> 44 24.00 0 56 0 0
#> 132 24.00 0 55 0 0
#> 83 24.00 0 6 0 0
#> 120.1 24.00 0 68 0 1
#> 74 24.00 0 43 0 1
#> 143 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 148.1 24.00 0 61 1 0
#> 11 24.00 0 42 0 1
#> 9 24.00 0 31 1 0
#> 143.1 24.00 0 51 0 0
#> 62.1 24.00 0 71 0 0
#> 176.1 24.00 0 43 0 1
#> 94 24.00 0 51 0 1
#> 20.2 24.00 0 46 1 0
#> 28 24.00 0 67 1 0
#> 165 24.00 0 47 0 0
#> 65.1 24.00 0 57 1 0
#> 21.1 24.00 0 47 0 0
#> 104.2 24.00 0 50 1 0
#> 35 24.00 0 51 0 0
#> 83.1 24.00 0 6 0 0
#> 94.1 24.00 0 51 0 1
#> 182 24.00 0 35 0 0
#> 174.1 24.00 0 49 1 0
#> 102 24.00 0 49 0 0
#> 137.1 24.00 0 45 1 0
#> 84 24.00 0 39 0 1
#> 165.1 24.00 0 47 0 0
#> 135.1 24.00 0 58 1 0
#> 84.1 24.00 0 39 0 1
#> 112 24.00 0 61 0 0
#> 47 24.00 0 38 0 1
#> 102.1 24.00 0 49 0 0
#> 185.1 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 143.2 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#> 34 24.00 0 36 0 0
#> 162 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 182.1 24.00 0 35 0 0
#> 82 24.00 0 34 0 0
#> 33.1 24.00 0 53 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.828 NA NA NA
#> 2 age, Cure model 0.0102 NA NA NA
#> 3 grade_ii, Cure model 0.466 NA NA NA
#> 4 grade_iii, Cure model 1.23 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0227 NA NA NA
#> 2 grade_ii, Survival model 0.333 NA NA NA
#> 3 grade_iii, Survival model 0.285 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.82803 0.01016 0.46646 1.23115
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 266.1
#> Residual Deviance: 253.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.82803321 0.01016474 0.46646189 1.23114772
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.02266937 0.33285823 0.28467699
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3969506 0.5930176 0.9048228 0.9786853 0.9358303 0.8215751 0.9688259
#> [8] 0.9908254 0.9554750 0.5576243 0.8345027 0.7148306 0.8737898 0.2026906
#> [15] 0.7008956 0.9176159 0.8880931 0.8949024 0.8810270 0.9387611 0.9688259
#> [22] 0.8171129 0.8588191 0.9015445 0.6043786 0.8427610 0.2026906 0.9269853
#> [29] 0.8548572 0.5576243 0.4804733 0.8080722 0.6043786 0.9908254 0.8302637
#> [36] 0.9207598 0.7690113 0.7843329 0.8259535 0.8845747 0.9238952 0.9835794
#> [43] 0.9387611 0.8588191 0.9269853 0.6437704 0.9080798 0.7792691 0.8737898
#> [50] 0.8588191 0.8080722 0.5415509 0.6859546 0.6529659 0.3562230 0.7148306
#> [57] 0.7893439 0.5222282 0.4804733 0.6529659 0.7148306 0.8700699 0.9080798
#> [64] 0.8880931 0.6859546 0.7575751 0.9472765 0.9472765 0.6245377 0.8468320
#> [71] 0.8468320 0.8034670 0.9662079 0.4540924 0.9269853 0.7893439 0.7458008
#> [78] 0.9144593 0.9860188 0.7893439 0.8982433 0.7397887 0.7458008 0.7690113
#> [85] 0.3969506 0.3092765 0.6529659 0.9581866 0.7575751 0.9884280 0.7336978
#> [92] 0.9786853 0.5576243 0.7008956 0.9387611 0.9908254 0.9908254 0.8345027
#> [99] 0.9635534 0.6781045 0.9608743 0.9688259 0.9472765 0.6343446 0.9688259
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 63 36 96 149 56 45 183 91 107 153 171 76 26
#> 22.77 21.19 14.54 8.37 12.21 17.42 9.24 5.33 11.18 21.33 16.57 19.22 15.77
#> 24 55 81 167 29 125 49 183.1 111 79 157 90 130
#> 23.89 19.34 14.06 15.55 15.45 15.65 12.19 9.24 17.45 16.23 15.10 20.94 16.47
#> 24.1 177 5 153.1 194 117 90.1 91.1 106 155 51 40 23
#> 23.89 12.53 16.43 21.33 22.40 17.46 20.94 5.33 16.67 13.08 18.23 18.00 16.92
#> 39 140 70 49.1 79.1 177.1 68 57 41 26.1 79.2 117.1 197
#> 15.59 12.68 7.38 12.19 16.23 12.53 20.62 14.46 18.02 15.77 16.23 17.46 21.60
#> 166 150 113 76.1 134 136 194.1 150.1 76.2 100 57.1 167.1 166.1
#> 19.98 20.33 22.86 19.22 17.81 21.83 22.40 20.33 19.22 16.07 14.46 15.55 19.98
#> 88 43 43.1 32 85 85.1 110 145 169 177.2 134.1 8 13
#> 18.37 12.10 12.10 20.90 16.44 16.44 17.56 10.07 22.41 12.53 17.81 18.43 14.34
#> 77 134.2 18 179 8.1 51.1 63.1 69 150.2 159 88.1 25 97
#> 7.27 17.81 15.21 18.63 18.43 18.23 22.77 23.23 20.33 10.55 18.37 6.32 19.14
#> 149.1 153.2 58 49.2 91.2 91.3 171.1 52 158 10 183.2 43.2 190
#> 8.37 21.33 19.34 12.19 5.33 5.33 16.57 10.42 20.14 10.53 9.24 12.10 20.81
#> 183.3 176 20 135 71 122 33 178 64 20.1 126 104 178.1
#> 9.24 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 62 103 161 54 67 137 185 174 67.1 46 80 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 54.1 109 72 104.1 141 67.2 65 21 103.1 172 148 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 142 7 44 132 83 120.1 74 143 118 116 148.1 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 143.1 62.1 176.1 94 20.2 28 165 65.1 21.1 104.2 35 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 182 174.1 102 137.1 84 165.1 135.1 84.1 112 47 102.1 185.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 53 143.2 163 200 34 162 119 182.1 82 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[24]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01004768 0.26687182 -0.06572291
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.48476791 0.01012333 0.05580768
#> grade_iii, Cure model
#> 0.45069105
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 136 21.83 1 43 0 1
#> 129 23.41 1 53 1 0
#> 177 12.53 1 75 0 0
#> 61 10.12 1 36 0 1
#> 55 19.34 1 69 0 1
#> 90 20.94 1 50 0 1
#> 68 20.62 1 44 0 0
#> 154 12.63 1 20 1 0
#> 124 9.73 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 86.1 23.81 1 58 0 1
#> 130 16.47 1 53 0 1
#> 181 16.46 1 45 0 1
#> 113 22.86 1 34 0 0
#> 8 18.43 1 32 0 0
#> 63 22.77 1 31 1 0
#> 183 9.24 1 67 1 0
#> 153 21.33 1 55 1 0
#> 57 14.46 1 45 0 1
#> 4 17.64 1 NA 0 1
#> 63.1 22.77 1 31 1 0
#> 187 9.92 1 39 1 0
#> 166 19.98 1 48 0 0
#> 145 10.07 1 65 1 0
#> 5 16.43 1 51 0 1
#> 85 16.44 1 36 0 0
#> 124.1 9.73 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 136.1 21.83 1 43 0 1
#> 170 19.54 1 43 0 1
#> 194 22.40 1 38 0 1
#> 81 14.06 1 34 0 0
#> 140 12.68 1 59 1 0
#> 159 10.55 1 50 0 1
#> 81.1 14.06 1 34 0 0
#> 91 5.33 1 61 0 1
#> 136.2 21.83 1 43 0 1
#> 39 15.59 1 37 0 1
#> 93 10.33 1 52 0 1
#> 199 19.81 1 NA 0 1
#> 164 23.60 1 76 0 1
#> 91.1 5.33 1 61 0 1
#> 157 15.10 1 47 0 0
#> 108 18.29 1 39 0 1
#> 150 20.33 1 48 0 0
#> 199.1 19.81 1 NA 0 1
#> 32 20.90 1 37 1 0
#> 157.1 15.10 1 47 0 0
#> 5.1 16.43 1 51 0 1
#> 58 19.34 1 39 0 0
#> 81.2 14.06 1 34 0 0
#> 88 18.37 1 47 0 0
#> 128 20.35 1 35 0 1
#> 23 16.92 1 61 0 0
#> 61.1 10.12 1 36 0 1
#> 79 16.23 1 54 1 0
#> 86.2 23.81 1 58 0 1
#> 187.1 9.92 1 39 1 0
#> 97 19.14 1 65 0 1
#> 168 23.72 1 70 0 0
#> 92 22.92 1 47 0 1
#> 157.2 15.10 1 47 0 0
#> 14.1 12.89 1 21 0 0
#> 117 17.46 1 26 0 1
#> 167 15.55 1 56 1 0
#> 177.1 12.53 1 75 0 0
#> 55.1 19.34 1 69 0 1
#> 192 16.44 1 31 1 0
#> 70 7.38 1 30 1 0
#> 136.3 21.83 1 43 0 1
#> 111 17.45 1 47 0 1
#> 39.1 15.59 1 37 0 1
#> 179 18.63 1 42 0 0
#> 58.1 19.34 1 39 0 0
#> 114 13.68 1 NA 0 0
#> 133 14.65 1 57 0 0
#> 18 15.21 1 49 1 0
#> 168.1 23.72 1 70 0 0
#> 179.1 18.63 1 42 0 0
#> 158 20.14 1 74 1 0
#> 14.2 12.89 1 21 0 0
#> 114.1 13.68 1 NA 0 0
#> 55.2 19.34 1 69 0 1
#> 187.2 9.92 1 39 1 0
#> 61.2 10.12 1 36 0 1
#> 99 21.19 1 38 0 1
#> 175 21.91 1 43 0 0
#> 99.1 21.19 1 38 0 1
#> 195 11.76 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 153.1 21.33 1 55 1 0
#> 29 15.45 1 68 1 0
#> 192.1 16.44 1 31 1 0
#> 189 10.51 1 NA 1 0
#> 171 16.57 1 41 0 1
#> 42 12.43 1 49 0 1
#> 81.3 14.06 1 34 0 0
#> 89 11.44 1 NA 0 0
#> 169 22.41 1 46 0 0
#> 197 21.60 1 69 1 0
#> 88.1 18.37 1 47 0 0
#> 24 23.89 1 38 0 0
#> 170.1 19.54 1 43 0 1
#> 8.1 18.43 1 32 0 0
#> 32.1 20.90 1 37 1 0
#> 96 14.54 1 33 0 1
#> 25 6.32 1 34 1 0
#> 125 15.65 1 67 1 0
#> 149 8.37 1 33 1 0
#> 177.2 12.53 1 75 0 0
#> 55.3 19.34 1 69 0 1
#> 100 16.07 1 60 0 0
#> 152 24.00 0 36 0 1
#> 198 24.00 0 66 0 1
#> 165 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 84 24.00 0 39 0 1
#> 31 24.00 0 36 0 1
#> 46 24.00 0 71 0 0
#> 152.1 24.00 0 36 0 1
#> 173 24.00 0 19 0 1
#> 80 24.00 0 41 0 0
#> 138 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 80.1 24.00 0 41 0 0
#> 142 24.00 0 53 0 0
#> 53 24.00 0 32 0 1
#> 87 24.00 0 27 0 0
#> 162 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 120 24.00 0 68 0 1
#> 71 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 118 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 103 24.00 0 56 1 0
#> 198.1 24.00 0 66 0 1
#> 98 24.00 0 34 1 0
#> 174 24.00 0 49 1 0
#> 137 24.00 0 45 1 0
#> 152.2 24.00 0 36 0 1
#> 147 24.00 0 76 1 0
#> 104 24.00 0 50 1 0
#> 67 24.00 0 25 0 0
#> 75 24.00 0 21 1 0
#> 31.1 24.00 0 36 0 1
#> 12 24.00 0 63 0 0
#> 33 24.00 0 53 0 0
#> 102 24.00 0 49 0 0
#> 109 24.00 0 48 0 0
#> 17.1 24.00 0 38 0 1
#> 67.1 24.00 0 25 0 0
#> 87.1 24.00 0 27 0 0
#> 83 24.00 0 6 0 0
#> 104.1 24.00 0 50 1 0
#> 80.2 24.00 0 41 0 0
#> 200 24.00 0 64 0 0
#> 75.1 24.00 0 21 1 0
#> 7 24.00 0 37 1 0
#> 47 24.00 0 38 0 1
#> 17.2 24.00 0 38 0 1
#> 19 24.00 0 57 0 1
#> 94.1 24.00 0 51 0 1
#> 172 24.00 0 41 0 0
#> 7.1 24.00 0 37 1 0
#> 143 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 152.3 24.00 0 36 0 1
#> 83.1 24.00 0 6 0 0
#> 172.1 24.00 0 41 0 0
#> 122 24.00 0 66 0 0
#> 142.1 24.00 0 53 0 0
#> 9 24.00 0 31 1 0
#> 165.1 24.00 0 47 0 0
#> 54 24.00 0 53 1 0
#> 148 24.00 0 61 1 0
#> 118.1 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 196 24.00 0 19 0 0
#> 186 24.00 0 45 1 0
#> 115 24.00 0 NA 1 0
#> 176 24.00 0 43 0 1
#> 72 24.00 0 40 0 1
#> 174.1 24.00 0 49 1 0
#> 147.1 24.00 0 76 1 0
#> 196.1 24.00 0 19 0 0
#> 1 24.00 0 23 1 0
#> 152.4 24.00 0 36 0 1
#> 62 24.00 0 71 0 0
#> 141 24.00 0 44 1 0
#> 94.2 24.00 0 51 0 1
#> 109.1 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 118.2 24.00 0 44 1 0
#> 137.1 24.00 0 45 1 0
#> 120.1 24.00 0 68 0 1
#> 135 24.00 0 58 1 0
#> 80.3 24.00 0 41 0 0
#> 131 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.485 NA NA NA
#> 2 age, Cure model 0.0101 NA NA NA
#> 3 grade_ii, Cure model 0.0558 NA NA NA
#> 4 grade_iii, Cure model 0.451 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0100 NA NA NA
#> 2 grade_ii, Survival model 0.267 NA NA NA
#> 3 grade_iii, Survival model -0.0657 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.48477 0.01012 0.05581 0.45069
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 257.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.48476791 0.01012333 0.05580768 0.45069105
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01004768 0.26687182 -0.06572291
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0567576046 0.0171478885 0.7195210329 0.8007807498 0.1888820369
#> [6] 0.1123888710 0.1338607206 0.7063438355 0.0018592618 0.0018592618
#> [11] 0.3590942758 0.3699601667 0.0262006342 0.2676043182 0.0311882883
#> [16] 0.8987539128 0.0857227045 0.5913756089 0.0311882883 0.8566273961
#> [21] 0.1645513665 0.8424320797 0.4133593552 0.3809566199 0.6545172823
#> [26] 0.0567576046 0.1725924814 0.0457041924 0.6040819009 0.6931498739
#> [31] 0.7731366761 0.6040819009 0.9707971860 0.0567576046 0.4704237499
#> [36] 0.7869047318 0.0130650189 0.9707971860 0.5299132917 0.3068074214
#> [41] 0.1489124323 0.1196364483 0.5299132917 0.4133593552 0.1888820369
#> [46] 0.6040819009 0.2869537582 0.1413181691 0.3377784461 0.8007807498
#> [51] 0.4357751716 0.0018592618 0.8566273961 0.2392110900 0.0070487009
#> [56] 0.0214751410 0.5299132917 0.6545172823 0.3170236849 0.4938605429
#> [61] 0.7195210329 0.1888820369 0.3809566199 0.9274550451 0.0567576046
#> [66] 0.3273326195 0.4704237499 0.2486324854 0.1888820369 0.5662711016
#> [71] 0.5178256817 0.0070487009 0.2486324854 0.1566578903 0.6545172823
#> [76] 0.1888820369 0.8566273961 0.8007807498 0.0987302833 0.0511259500
#> [81] 0.0987302833 0.9418202371 0.0857227045 0.5057947701 0.3809566199
#> [86] 0.3483744399 0.7594740728 0.6040819009 0.0405053902 0.0792091039
#> [91] 0.2869537582 0.0004296619 0.1725924814 0.2676043182 0.1196364483
#> [96] 0.5787787254 0.9563008047 0.4587642187 0.9130974115 0.7195210329
#> [101] 0.1888820369 0.4472028106 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 136 129 177 61 55 90 68 154 86 86.1 130 181 113
#> 21.83 23.41 12.53 10.12 19.34 20.94 20.62 12.63 23.81 23.81 16.47 16.46 22.86
#> 8 63 183 153 57 63.1 187 166 145 5 85 14 136.1
#> 18.43 22.77 9.24 21.33 14.46 22.77 9.92 19.98 10.07 16.43 16.44 12.89 21.83
#> 170 194 81 140 159 81.1 91 136.2 39 93 164 91.1 157
#> 19.54 22.40 14.06 12.68 10.55 14.06 5.33 21.83 15.59 10.33 23.60 5.33 15.10
#> 108 150 32 157.1 5.1 58 81.2 88 128 23 61.1 79 86.2
#> 18.29 20.33 20.90 15.10 16.43 19.34 14.06 18.37 20.35 16.92 10.12 16.23 23.81
#> 187.1 97 168 92 157.2 14.1 117 167 177.1 55.1 192 70 136.3
#> 9.92 19.14 23.72 22.92 15.10 12.89 17.46 15.55 12.53 19.34 16.44 7.38 21.83
#> 111 39.1 179 58.1 133 18 168.1 179.1 158 14.2 55.2 187.2 61.2
#> 17.45 15.59 18.63 19.34 14.65 15.21 23.72 18.63 20.14 12.89 19.34 9.92 10.12
#> 99 175 99.1 77 153.1 29 192.1 171 42 81.3 169 197 88.1
#> 21.19 21.91 21.19 7.27 21.33 15.45 16.44 16.57 12.43 14.06 22.41 21.60 18.37
#> 24 170.1 8.1 32.1 96 25 125 149 177.2 55.3 100 152 198
#> 23.89 19.54 18.43 20.90 14.54 6.32 15.65 8.37 12.53 19.34 16.07 24.00 24.00
#> 165 94 84 31 46 152.1 173 80 138 11 80.1 142 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 162 112 120 71 17 118 74 64 103 198.1 98 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 152.2 147 104 67 75 31.1 12 33 102 109 17.1 67.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 83 104.1 80.2 200 75.1 7 47 17.2 19 94.1 172 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 126 152.3 83.1 172.1 122 142.1 9 165.1 54 148 118.1 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 186 176 72 174.1 147.1 196.1 1 152.4 62 141 94.2 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 118.2 137.1 120.1 135 80.3 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[25]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01221035 0.53767281 0.31080337
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.69816816 0.01616128 -0.22174839
#> grade_iii, Cure model
#> 0.69462869
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 15 22.68 1 48 0 0
#> 127 3.53 1 62 0 1
#> 189 10.51 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 51 18.23 1 83 0 1
#> 93 10.33 1 52 0 1
#> 16 8.71 1 71 0 1
#> 30 17.43 1 78 0 0
#> 110 17.56 1 65 0 1
#> 108 18.29 1 39 0 1
#> 99 21.19 1 38 0 1
#> 8 18.43 1 32 0 0
#> 180 14.82 1 37 0 0
#> 145 10.07 1 65 1 0
#> 32 20.90 1 37 1 0
#> 29 15.45 1 68 1 0
#> 133 14.65 1 57 0 0
#> 18 15.21 1 49 1 0
#> 158 20.14 1 74 1 0
#> 130 16.47 1 53 0 1
#> 61 10.12 1 36 0 1
#> 117 17.46 1 26 0 1
#> 57 14.46 1 45 0 1
#> 68 20.62 1 44 0 0
#> 150 20.33 1 48 0 0
#> 14 12.89 1 21 0 0
#> 10 10.53 1 34 0 0
#> 14.1 12.89 1 21 0 0
#> 4 17.64 1 NA 0 1
#> 155 13.08 1 26 0 0
#> 124 9.73 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 77 7.27 1 67 0 1
#> 180.1 14.82 1 37 0 0
#> 123 13.00 1 44 1 0
#> 101 9.97 1 10 0 1
#> 195 11.76 1 NA 1 0
#> 110.1 17.56 1 65 0 1
#> 52 10.42 1 52 0 1
#> 183 9.24 1 67 1 0
#> 15.1 22.68 1 48 0 0
#> 85 16.44 1 36 0 0
#> 4.1 17.64 1 NA 0 1
#> 167 15.55 1 56 1 0
#> 59 10.16 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 105 19.75 1 60 0 0
#> 136 21.83 1 43 0 1
#> 50 10.02 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 189.1 10.51 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 66 22.13 1 53 0 0
#> 86 23.81 1 58 0 1
#> 24 23.89 1 38 0 0
#> 105.1 19.75 1 60 0 0
#> 194 22.40 1 38 0 1
#> 43 12.10 1 61 0 1
#> 190 20.81 1 42 1 0
#> 41 18.02 1 40 1 0
#> 69 23.23 1 25 0 1
#> 192.1 16.44 1 31 1 0
#> 68.1 20.62 1 44 0 0
#> 190.1 20.81 1 42 1 0
#> 59.1 10.16 1 NA 1 0
#> 61.1 10.12 1 36 0 1
#> 89 11.44 1 NA 0 0
#> 170 19.54 1 43 0 1
#> 130.1 16.47 1 53 0 1
#> 169 22.41 1 46 0 0
#> 8.1 18.43 1 32 0 0
#> 149 8.37 1 33 1 0
#> 179 18.63 1 42 0 0
#> 56 12.21 1 60 0 0
#> 101.1 9.97 1 10 0 1
#> 129 23.41 1 53 1 0
#> 81 14.06 1 34 0 0
#> 13 14.34 1 54 0 1
#> 164.1 23.60 1 76 0 1
#> 111 17.45 1 47 0 1
#> 56.1 12.21 1 60 0 0
#> 66.1 22.13 1 53 0 0
#> 6 15.64 1 39 0 0
#> 157 15.10 1 47 0 0
#> 57.1 14.46 1 45 0 1
#> 50.1 10.02 1 NA 1 0
#> 111.1 17.45 1 47 0 1
#> 86.1 23.81 1 58 0 1
#> 96 14.54 1 33 0 1
#> 56.2 12.21 1 60 0 0
#> 5 16.43 1 51 0 1
#> 51.1 18.23 1 83 0 1
#> 25 6.32 1 34 1 0
#> 108.1 18.29 1 39 0 1
#> 139 21.49 1 63 1 0
#> 158.1 20.14 1 74 1 0
#> 49 12.19 1 48 1 0
#> 111.2 17.45 1 47 0 1
#> 23 16.92 1 61 0 0
#> 108.2 18.29 1 39 0 1
#> 183.1 9.24 1 67 1 0
#> 110.2 17.56 1 65 0 1
#> 184 17.77 1 38 0 0
#> 78 23.88 1 43 0 0
#> 29.1 15.45 1 68 1 0
#> 57.2 14.46 1 45 0 1
#> 41.1 18.02 1 40 1 0
#> 158.2 20.14 1 74 1 0
#> 66.2 22.13 1 53 0 0
#> 150.1 20.33 1 48 0 0
#> 81.1 14.06 1 34 0 0
#> 168 23.72 1 70 0 0
#> 62 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 82 24.00 0 34 0 0
#> 7 24.00 0 37 1 0
#> 80 24.00 0 41 0 0
#> 71 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 64 24.00 0 43 0 0
#> 163 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 118 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 33 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 44 24.00 0 56 0 0
#> 200 24.00 0 64 0 0
#> 31 24.00 0 36 0 1
#> 62.1 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 148 24.00 0 61 1 0
#> 173.1 24.00 0 19 0 1
#> 143 24.00 0 51 0 0
#> 64.1 24.00 0 43 0 0
#> 38 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 65 24.00 0 57 1 0
#> 115.1 24.00 0 NA 1 0
#> 87 24.00 0 27 0 0
#> 185 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 118.1 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 21 24.00 0 47 0 0
#> 185.1 24.00 0 44 1 0
#> 200.1 24.00 0 64 0 0
#> 3 24.00 0 31 1 0
#> 67.1 24.00 0 25 0 0
#> 115.2 24.00 0 NA 1 0
#> 65.1 24.00 0 57 1 0
#> 73 24.00 0 NA 0 1
#> 73.1 24.00 0 NA 0 1
#> 118.2 24.00 0 44 1 0
#> 115.3 24.00 0 NA 1 0
#> 162.1 24.00 0 51 0 0
#> 7.1 24.00 0 37 1 0
#> 98 24.00 0 34 1 0
#> 48 24.00 0 31 1 0
#> 64.2 24.00 0 43 0 0
#> 116.1 24.00 0 58 0 1
#> 102 24.00 0 49 0 0
#> 28 24.00 0 67 1 0
#> 44.1 24.00 0 56 0 0
#> 102.1 24.00 0 49 0 0
#> 135 24.00 0 58 1 0
#> 19.1 24.00 0 57 0 1
#> 148.1 24.00 0 61 1 0
#> 132 24.00 0 55 0 0
#> 1 24.00 0 23 1 0
#> 64.3 24.00 0 43 0 0
#> 38.1 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 174 24.00 0 49 1 0
#> 33.1 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 80.1 24.00 0 41 0 0
#> 31.1 24.00 0 36 0 1
#> 104 24.00 0 50 1 0
#> 163.1 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 48.1 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 173.2 24.00 0 19 0 1
#> 2 24.00 0 9 0 0
#> 163.2 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 120 24.00 0 68 0 1
#> 173.3 24.00 0 19 0 1
#> 98.1 24.00 0 34 1 0
#> 196 24.00 0 19 0 0
#> 143.1 24.00 0 51 0 0
#> 19.2 24.00 0 57 0 1
#> 173.4 24.00 0 19 0 1
#> 146 24.00 0 63 1 0
#> 31.2 24.00 0 36 0 1
#> 87.1 24.00 0 27 0 0
#> 48.2 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.698 NA NA NA
#> 2 age, Cure model 0.0162 NA NA NA
#> 3 grade_ii, Cure model -0.222 NA NA NA
#> 4 grade_iii, Cure model 0.695 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0122 NA NA NA
#> 2 grade_ii, Survival model 0.538 NA NA NA
#> 3 grade_iii, Survival model 0.311 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.69817 0.01616 -0.22175 0.69463
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 251.7
#> Residual Deviance: 243.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.69816816 0.01616128 -0.22174839 0.69462869
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01221035 0.53767281 0.31080337
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0330230470 0.9866682827 0.7273829427 0.2665494476 0.8292856690
#> [6] 0.9336476576 0.3885700024 0.3162319331 0.2384434233 0.0902566696
#> [11] 0.2196641312 0.5454868087 0.8683831571 0.0977484149 0.4994680208
#> [16] 0.5689148275 0.5222799898 0.1504072749 0.4105077285 0.8423534476
#> [21] 0.3468175764 0.5928604689 0.1194987677 0.1345591373 0.6900327393
#> [26] 0.8033208056 0.6900327393 0.6652067504 0.4326422222 0.9601103021
#> [31] 0.5454868087 0.6776197892 0.8815419160 0.3162319331 0.8162746543
#> [36] 0.9075033209 0.0330230470 0.4326422222 0.4880625277 0.7148354339
#> [41] 0.1746917779 0.0755829924 0.0139678823 0.2011573900 0.0561307738
#> [46] 0.0045831816 0.0004116871 0.1746917779 0.0499089650 0.7904375441
#> [51] 0.1051893155 0.2863482885 0.0279304891 0.4326422222 0.1194987677
#> [56] 0.1051893155 0.8423534476 0.1921431499 0.4105077285 0.0437962260
#> [61] 0.2196641312 0.9468923112 0.2103290823 0.7398570674 0.8815419160
#> [66] 0.0228353875 0.6407353580 0.6285403865 0.0139678823 0.3573302420
#> [71] 0.7398570674 0.0561307738 0.4766931615 0.5338283307 0.5928604689
#> [76] 0.3573302420 0.0045831816 0.5808767833 0.7398570674 0.4654256174
#> [81] 0.2665494476 0.9734010966 0.2384434233 0.0828525150 0.1504072749
#> [86] 0.7776277999 0.3573302420 0.3994597730 0.2384434233 0.9075033209
#> [91] 0.3162319331 0.3060788171 0.0020196424 0.4994680208 0.5928604689
#> [96] 0.2863482885 0.1504072749 0.0561307738 0.1345591373 0.6407353580
#> [101] 0.0099970850 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 15 127 154 51 93 16 30 110 108 99 8 180 145
#> 22.68 3.53 12.63 18.23 10.33 8.71 17.43 17.56 18.29 21.19 18.43 14.82 10.07
#> 32 29 133 18 158 130 61 117 57 68 150 14 10
#> 20.90 15.45 14.65 15.21 20.14 16.47 10.12 17.46 14.46 20.62 20.33 12.89 10.53
#> 14.1 155 192 77 180.1 123 101 110.1 52 183 15.1 85 167
#> 12.89 13.08 16.44 7.27 14.82 13.00 9.97 17.56 10.42 9.24 22.68 16.44 15.55
#> 140 105 136 164 97 66 86 24 105.1 194 43 190 41
#> 12.68 19.75 21.83 23.60 19.14 22.13 23.81 23.89 19.75 22.40 12.10 20.81 18.02
#> 69 192.1 68.1 190.1 61.1 170 130.1 169 8.1 149 179 56 101.1
#> 23.23 16.44 20.62 20.81 10.12 19.54 16.47 22.41 18.43 8.37 18.63 12.21 9.97
#> 129 81 13 164.1 111 56.1 66.1 6 157 57.1 111.1 86.1 96
#> 23.41 14.06 14.34 23.60 17.45 12.21 22.13 15.64 15.10 14.46 17.45 23.81 14.54
#> 56.2 5 51.1 25 108.1 139 158.1 49 111.2 23 108.2 183.1 110.2
#> 12.21 16.43 18.23 6.32 18.29 21.49 20.14 12.19 17.45 16.92 18.29 9.24 17.56
#> 184 78 29.1 57.2 41.1 158.2 66.2 150.1 81.1 168 62 173 82
#> 17.77 23.88 15.45 14.46 18.02 20.14 22.13 20.33 14.06 23.72 24.00 24.00 24.00
#> 7 80 71 116 64 163 67 118 152 33 178 44 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 62.1 148 173.1 143 64.1 38 193 65 87 185 186 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 19 21 185.1 200.1 3 67.1 65.1 118.2 162.1 7.1 98 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.2 116.1 102 28 44.1 102.1 135 19.1 148.1 132 1 64.3 38.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 174 33.1 198 80.1 31.1 104 163.1 137 48.1 46 173.2 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163.2 74 121 120 173.3 98.1 196 143.1 19.2 173.4 146 31.2 87.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.2
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[26]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01402458 0.48895844 0.48631105
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.16412074 0.02149333 0.33333317
#> grade_iii, Cure model
#> 0.68683428
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 187 9.92 1 39 1 0
#> 25 6.32 1 34 1 0
#> 57 14.46 1 45 0 1
#> 158 20.14 1 74 1 0
#> 49 12.19 1 48 1 0
#> 150 20.33 1 48 0 0
#> 129 23.41 1 53 1 0
#> 139 21.49 1 63 1 0
#> 134 17.81 1 47 1 0
#> 18 15.21 1 49 1 0
#> 52 10.42 1 52 0 1
#> 18.1 15.21 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 133 14.65 1 57 0 0
#> 56 12.21 1 60 0 0
#> 4 17.64 1 NA 0 1
#> 10 10.53 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 150.1 20.33 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 145 10.07 1 65 1 0
#> 5 16.43 1 51 0 1
#> 199 19.81 1 NA 0 1
#> 32 20.90 1 37 1 0
#> 183 9.24 1 67 1 0
#> 78 23.88 1 43 0 0
#> 51 18.23 1 83 0 1
#> 133.1 14.65 1 57 0 0
#> 166 19.98 1 48 0 0
#> 179 18.63 1 42 0 0
#> 79 16.23 1 54 1 0
#> 61 10.12 1 36 0 1
#> 66 22.13 1 53 0 0
#> 175 21.91 1 43 0 0
#> 79.1 16.23 1 54 1 0
#> 86 23.81 1 58 0 1
#> 43 12.10 1 61 0 1
#> 189.1 10.51 1 NA 1 0
#> 78.1 23.88 1 43 0 0
#> 127 3.53 1 62 0 1
#> 52.1 10.42 1 52 0 1
#> 40 18.00 1 28 1 0
#> 113 22.86 1 34 0 0
#> 26 15.77 1 49 0 1
#> 180 14.82 1 37 0 0
#> 16 8.71 1 71 0 1
#> 170 19.54 1 43 0 1
#> 18.2 15.21 1 49 1 0
#> 60 13.15 1 38 1 0
#> 32.1 20.90 1 37 1 0
#> 99.1 21.19 1 38 0 1
#> 29 15.45 1 68 1 0
#> 167 15.55 1 56 1 0
#> 63.1 22.77 1 31 1 0
#> 23 16.92 1 61 0 0
#> 90 20.94 1 50 0 1
#> 25.1 6.32 1 34 1 0
#> 93 10.33 1 52 0 1
#> 43.1 12.10 1 61 0 1
#> 97 19.14 1 65 0 1
#> 133.2 14.65 1 57 0 0
#> 76 19.22 1 54 0 1
#> 79.2 16.23 1 54 1 0
#> 166.1 19.98 1 48 0 0
#> 169 22.41 1 46 0 0
#> 171 16.57 1 41 0 1
#> 5.1 16.43 1 51 0 1
#> 123 13.00 1 44 1 0
#> 194 22.40 1 38 0 1
#> 60.1 13.15 1 38 1 0
#> 108 18.29 1 39 0 1
#> 105 19.75 1 60 0 0
#> 136 21.83 1 43 0 1
#> 97.1 19.14 1 65 0 1
#> 183.1 9.24 1 67 1 0
#> 26.1 15.77 1 49 0 1
#> 99.2 21.19 1 38 0 1
#> 42 12.43 1 49 0 1
#> 166.2 19.98 1 48 0 0
#> 42.1 12.43 1 49 0 1
#> 56.1 12.21 1 60 0 0
#> 190 20.81 1 42 1 0
#> 29.1 15.45 1 68 1 0
#> 78.2 23.88 1 43 0 0
#> 41 18.02 1 40 1 0
#> 59 10.16 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 175.1 21.91 1 43 0 0
#> 63.2 22.77 1 31 1 0
#> 13 14.34 1 54 0 1
#> 183.2 9.24 1 67 1 0
#> 23.1 16.92 1 61 0 0
#> 45 17.42 1 54 0 1
#> 56.2 12.21 1 60 0 0
#> 100 16.07 1 60 0 0
#> 158.1 20.14 1 74 1 0
#> 175.2 21.91 1 43 0 0
#> 6 15.64 1 39 0 0
#> 81 14.06 1 34 0 0
#> 110 17.56 1 65 0 1
#> 129.1 23.41 1 53 1 0
#> 79.3 16.23 1 54 1 0
#> 51.1 18.23 1 83 0 1
#> 101 9.97 1 10 0 1
#> 107 11.18 1 54 1 0
#> 29.2 15.45 1 68 1 0
#> 149 8.37 1 33 1 0
#> 149.1 8.37 1 33 1 0
#> 111 17.45 1 47 0 1
#> 71 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 103 24.00 0 56 1 0
#> 84 24.00 0 39 0 1
#> 148 24.00 0 61 1 0
#> 112 24.00 0 61 0 0
#> 119 24.00 0 17 0 0
#> 2 24.00 0 9 0 0
#> 121 24.00 0 57 1 0
#> 182 24.00 0 35 0 0
#> 120 24.00 0 68 0 1
#> 160 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 83 24.00 0 6 0 0
#> 143 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 84.1 24.00 0 39 0 1
#> 103.1 24.00 0 56 1 0
#> 62 24.00 0 71 0 0
#> 17 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 109 24.00 0 48 0 0
#> 103.2 24.00 0 56 1 0
#> 95 24.00 0 68 0 1
#> 161 24.00 0 45 0 0
#> 103.3 24.00 0 56 1 0
#> 62.1 24.00 0 71 0 0
#> 151 24.00 0 42 0 0
#> 193 24.00 0 45 0 1
#> 162 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 3.1 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 121.1 24.00 0 57 1 0
#> 152.1 24.00 0 36 0 1
#> 53 24.00 0 32 0 1
#> 176 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 172 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#> 71.1 24.00 0 51 0 0
#> 193.1 24.00 0 45 0 1
#> 98 24.00 0 34 1 0
#> 162.1 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 80 24.00 0 41 0 0
#> 144 24.00 0 28 0 1
#> 33 24.00 0 53 0 0
#> 35 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 74 24.00 0 43 0 1
#> 141.1 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 146.1 24.00 0 63 1 0
#> 72.1 24.00 0 40 0 1
#> 126 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 162.2 24.00 0 51 0 0
#> 146.2 24.00 0 63 1 0
#> 161.1 24.00 0 45 0 0
#> 80.1 24.00 0 41 0 0
#> 138 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 34.1 24.00 0 36 0 0
#> 126.1 24.00 0 48 0 0
#> 156 24.00 0 50 1 0
#> 138.1 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 1 24.00 0 23 1 0
#> 71.2 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 161.2 24.00 0 45 0 0
#> 53.1 24.00 0 32 0 1
#> 174 24.00 0 49 1 0
#> 174.1 24.00 0 49 1 0
#> 35.1 24.00 0 51 0 0
#> 121.2 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 178 24.00 0 52 1 0
#> 172.1 24.00 0 41 0 0
#> 35.2 24.00 0 51 0 0
#> 84.2 24.00 0 39 0 1
#> 121.3 24.00 0 57 1 0
#> 119.1 24.00 0 17 0 0
#> 47.1 24.00 0 38 0 1
#> 156.1 24.00 0 50 1 0
#> 20.1 24.00 0 46 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.16 NA NA NA
#> 2 age, Cure model 0.0215 NA NA NA
#> 3 grade_ii, Cure model 0.333 NA NA NA
#> 4 grade_iii, Cure model 0.687 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0140 NA NA NA
#> 2 grade_ii, Survival model 0.489 NA NA NA
#> 3 grade_iii, Survival model 0.486 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.16412 0.02149 0.33333 0.68683
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 257.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.16412074 0.02149333 0.33333317 0.68683428
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01402458 0.48895844 0.48631105
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9669972 0.9903202 0.8839295 0.6217683 0.9272676 0.6038224 0.3143114
#> [8] 0.5220749 0.7434306 0.8546133 0.9457573 0.8546133 0.3769315 0.8715179
#> [15] 0.9158572 0.9421019 0.6767513 0.6038224 0.5339784 0.9600160 0.7882747
#> [22] 0.5754697 0.9704596 0.1630366 0.7188527 0.8715179 0.6380238 0.7053087
#> [29] 0.7986211 0.9564806 0.4556133 0.4700960 0.7986211 0.2817757 0.9310526
#> [36] 0.1630366 0.9967899 0.9457573 0.7373747 0.3561354 0.8227842 0.8672867
#> [43] 0.9804710 0.6691618 0.8546133 0.8961758 0.5754697 0.5339784 0.8415040
#> [50] 0.8368772 0.3769315 0.7665223 0.5652755 0.9903202 0.9529228 0.9310526
#> [57] 0.6916083 0.8715179 0.6842793 0.7986211 0.6380238 0.4246322 0.7774899
#> [64] 0.7882747 0.9041474 0.4406044 0.8961758 0.7121390 0.6613987 0.5093146
#> [71] 0.6916083 0.9704596 0.8227842 0.5339784 0.9081066 0.6380238 0.9081066
#> [78] 0.9158572 0.5945141 0.8415040 0.1630366 0.7312477 0.7829205 0.4700960
#> [85] 0.3769315 0.8880465 0.9704596 0.7665223 0.7609097 0.9158572 0.8179473
#> [92] 0.6217683 0.4700960 0.8321836 0.8921168 0.7493822 0.3143114 0.7986211
#> [99] 0.7188527 0.9635121 0.9384378 0.8415040 0.9837811 0.9837811 0.7551931
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 187 25 57 158 49 150 129 139 134 18 52 18.1 63
#> 9.92 6.32 14.46 20.14 12.19 20.33 23.41 21.49 17.81 15.21 10.42 15.21 22.77
#> 133 56 10 58 150.1 99 145 5 32 183 78 51 133.1
#> 14.65 12.21 10.53 19.34 20.33 21.19 10.07 16.43 20.90 9.24 23.88 18.23 14.65
#> 166 179 79 61 66 175 79.1 86 43 78.1 127 52.1 40
#> 19.98 18.63 16.23 10.12 22.13 21.91 16.23 23.81 12.10 23.88 3.53 10.42 18.00
#> 113 26 180 16 170 18.2 60 32.1 99.1 29 167 63.1 23
#> 22.86 15.77 14.82 8.71 19.54 15.21 13.15 20.90 21.19 15.45 15.55 22.77 16.92
#> 90 25.1 93 43.1 97 133.2 76 79.2 166.1 169 171 5.1 123
#> 20.94 6.32 10.33 12.10 19.14 14.65 19.22 16.23 19.98 22.41 16.57 16.43 13.00
#> 194 60.1 108 105 136 97.1 183.1 26.1 99.2 42 166.2 42.1 56.1
#> 22.40 13.15 18.29 19.75 21.83 19.14 9.24 15.77 21.19 12.43 19.98 12.43 12.21
#> 190 29.1 78.2 41 181 175.1 63.2 13 183.2 23.1 45 56.2 100
#> 20.81 15.45 23.88 18.02 16.46 21.91 22.77 14.34 9.24 16.92 17.42 12.21 16.07
#> 158.1 175.2 6 81 110 129.1 79.3 51.1 101 107 29.2 149 149.1
#> 20.14 21.91 15.64 14.06 17.56 23.41 16.23 18.23 9.97 11.18 15.45 8.37 8.37
#> 111 71 152 103 84 148 112 119 2 121 182 120 160
#> 17.45 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 143 3 84.1 103.1 62 17 141 34 109 103.2 95 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.3 62.1 151 193 162 47 3.1 163 121.1 152.1 53 176 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 185 71.1 193.1 98 162.1 72 80 144 33 35 31 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.1 102 146.1 72.1 126 147 162.2 146.2 161.1 80.1 138 46 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126.1 156 138.1 191 1 71.2 22 161.2 53.1 174 174.1 35.1 121.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 178 172.1 35.2 84.2 121.3 119.1 47.1 156.1 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[27]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01603757 0.25457957 -0.06721908
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.602566720 0.008491294 0.143733069
#> grade_iii, Cure model
#> 1.034905578
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 92 22.92 1 47 0 1
#> 96 14.54 1 33 0 1
#> 157 15.10 1 47 0 0
#> 88 18.37 1 47 0 0
#> 114 13.68 1 NA 0 0
#> 128 20.35 1 35 0 1
#> 89 11.44 1 NA 0 0
#> 180 14.82 1 37 0 0
#> 170 19.54 1 43 0 1
#> 96.1 14.54 1 33 0 1
#> 177 12.53 1 75 0 0
#> 139 21.49 1 63 1 0
#> 192 16.44 1 31 1 0
#> 171 16.57 1 41 0 1
#> 145 10.07 1 65 1 0
#> 51 18.23 1 83 0 1
#> 164 23.60 1 76 0 1
#> 180.1 14.82 1 37 0 0
#> 10 10.53 1 34 0 0
#> 197 21.60 1 69 1 0
#> 51.1 18.23 1 83 0 1
#> 51.2 18.23 1 83 0 1
#> 15 22.68 1 48 0 0
#> 86 23.81 1 58 0 1
#> 139.1 21.49 1 63 1 0
#> 192.1 16.44 1 31 1 0
#> 81 14.06 1 34 0 0
#> 55 19.34 1 69 0 1
#> 129 23.41 1 53 1 0
#> 136 21.83 1 43 0 1
#> 117 17.46 1 26 0 1
#> 180.2 14.82 1 37 0 0
#> 5 16.43 1 51 0 1
#> 101 9.97 1 10 0 1
#> 10.1 10.53 1 34 0 0
#> 10.2 10.53 1 34 0 0
#> 184 17.77 1 38 0 0
#> 123 13.00 1 44 1 0
#> 183 9.24 1 67 1 0
#> 86.1 23.81 1 58 0 1
#> 18 15.21 1 49 1 0
#> 127 3.53 1 62 0 1
#> 23 16.92 1 61 0 0
#> 81.1 14.06 1 34 0 0
#> 124 9.73 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 101.1 9.97 1 10 0 1
#> 157.1 15.10 1 47 0 0
#> 140 12.68 1 59 1 0
#> 134 17.81 1 47 1 0
#> 55.1 19.34 1 69 0 1
#> 70 7.38 1 30 1 0
#> 157.2 15.10 1 47 0 0
#> 55.2 19.34 1 69 0 1
#> 52 10.42 1 52 0 1
#> 136.1 21.83 1 43 0 1
#> 114.1 13.68 1 NA 0 0
#> 154 12.63 1 20 1 0
#> 108 18.29 1 39 0 1
#> 89.1 11.44 1 NA 0 0
#> 192.2 16.44 1 31 1 0
#> 170.1 19.54 1 43 0 1
#> 123.1 13.00 1 44 1 0
#> 63 22.77 1 31 1 0
#> 107 11.18 1 54 1 0
#> 99 21.19 1 38 0 1
#> 180.3 14.82 1 37 0 0
#> 169 22.41 1 46 0 0
#> 133 14.65 1 57 0 0
#> 60 13.15 1 38 1 0
#> 56 12.21 1 60 0 0
#> 52.1 10.42 1 52 0 1
#> 36 21.19 1 48 0 1
#> 199 19.81 1 NA 0 1
#> 96.2 14.54 1 33 0 1
#> 181 16.46 1 45 0 1
#> 18.1 15.21 1 49 1 0
#> 66 22.13 1 53 0 0
#> 114.2 13.68 1 NA 0 0
#> 111 17.45 1 47 0 1
#> 50 10.02 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 110 17.56 1 65 0 1
#> 123.2 13.00 1 44 1 0
#> 56.1 12.21 1 60 0 0
#> 89.2 11.44 1 NA 0 0
#> 70.1 7.38 1 30 1 0
#> 170.2 19.54 1 43 0 1
#> 36.1 21.19 1 48 0 1
#> 97 19.14 1 65 0 1
#> 127.1 3.53 1 62 0 1
#> 78 23.88 1 43 0 0
#> 129.1 23.41 1 53 1 0
#> 99.1 21.19 1 38 0 1
#> 125 15.65 1 67 1 0
#> 113 22.86 1 34 0 0
#> 16 8.71 1 71 0 1
#> 155 13.08 1 26 0 0
#> 183.1 9.24 1 67 1 0
#> 49 12.19 1 48 1 0
#> 14 12.89 1 21 0 0
#> 23.1 16.92 1 61 0 0
#> 184.1 17.77 1 38 0 0
#> 168 23.72 1 70 0 0
#> 105 19.75 1 60 0 0
#> 111.1 17.45 1 47 0 1
#> 150 20.33 1 48 0 0
#> 88.1 18.37 1 47 0 0
#> 159 10.55 1 50 0 1
#> 197.1 21.60 1 69 1 0
#> 50.1 10.02 1 NA 1 0
#> 199.1 19.81 1 NA 0 1
#> 119 24.00 0 17 0 0
#> 112 24.00 0 61 0 0
#> 147 24.00 0 76 1 0
#> 94 24.00 0 51 0 1
#> 47 24.00 0 38 0 1
#> 1 24.00 0 23 1 0
#> 196 24.00 0 19 0 0
#> 35 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 131 24.00 0 66 0 0
#> 126 24.00 0 48 0 0
#> 48 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 3 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 48.1 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 9 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 172 24.00 0 41 0 0
#> 17.1 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 193 24.00 0 45 0 1
#> 71 24.00 0 51 0 0
#> 71.1 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 72 24.00 0 40 0 1
#> 34 24.00 0 36 0 0
#> 142 24.00 0 53 0 0
#> 120 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 67 24.00 0 25 0 0
#> 119.1 24.00 0 17 0 0
#> 22 24.00 0 52 1 0
#> 65.1 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 20 24.00 0 46 1 0
#> 33 24.00 0 53 0 0
#> 2 24.00 0 9 0 0
#> 185 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 132.1 24.00 0 55 0 0
#> 102 24.00 0 49 0 0
#> 35.1 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 74 24.00 0 43 0 1
#> 34.1 24.00 0 36 0 0
#> 143 24.00 0 51 0 0
#> 1.1 24.00 0 23 1 0
#> 191.1 24.00 0 60 0 1
#> 151 24.00 0 42 0 0
#> 185.1 24.00 0 44 1 0
#> 131.1 24.00 0 66 0 0
#> 191.2 24.00 0 60 0 1
#> 80.1 24.00 0 41 0 0
#> 186 24.00 0 45 1 0
#> 148 24.00 0 61 1 0
#> 75 24.00 0 21 1 0
#> 38 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 65.2 24.00 0 57 1 0
#> 120.1 24.00 0 68 0 1
#> 35.2 24.00 0 51 0 0
#> 160.1 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 75.1 24.00 0 21 1 0
#> 163 24.00 0 66 0 0
#> 28 24.00 0 67 1 0
#> 80.2 24.00 0 41 0 0
#> 147.1 24.00 0 76 1 0
#> 103.1 24.00 0 56 1 0
#> 162 24.00 0 51 0 0
#> 193.1 24.00 0 45 0 1
#> 103.2 24.00 0 56 1 0
#> 152 24.00 0 36 0 1
#> 120.2 24.00 0 68 0 1
#> 67.1 24.00 0 25 0 0
#> 83 24.00 0 6 0 0
#> 102.1 24.00 0 49 0 0
#> 151.1 24.00 0 42 0 0
#> 3.1 24.00 0 31 1 0
#> 48.2 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 2.1 24.00 0 9 0 0
#> 20.1 24.00 0 46 1 0
#> 72.1 24.00 0 40 0 1
#> 178 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.603 NA NA NA
#> 2 age, Cure model 0.00849 NA NA NA
#> 3 grade_ii, Cure model 0.144 NA NA NA
#> 4 grade_iii, Cure model 1.03 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0160 NA NA NA
#> 2 grade_ii, Survival model 0.255 NA NA NA
#> 3 grade_iii, Survival model -0.0672 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.602567 0.008491 0.143733 1.034906
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 261.1
#> Residual Deviance: 250.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.602566720 0.008491294 0.143733069 1.034905578
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01603757 0.25457957 -0.06721908
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 4.034442e-03 4.276664e-01 3.280650e-01 9.689480e-02 4.558758e-02
#> [6] 3.641023e-01 5.892572e-02 4.276664e-01 6.150249e-01 2.504830e-02
#> [11] 2.508302e-01 2.297301e-01 8.143655e-01 1.170461e-01 1.188126e-03
#> [16] 3.641023e-01 7.284189e-01 1.945116e-02 1.170461e-01 1.170461e-01
#> [21] 8.613157e-03 1.248952e-04 2.504830e-02 2.508302e-01 4.683061e-01
#> [26] 7.356976e-02 2.045199e-03 1.464981e-02 1.818776e-01 3.641023e-01
#> [31] 2.823503e-01 8.323517e-01 7.284189e-01 7.284189e-01 1.560432e-01
#> [36] 5.255014e-01 8.682479e-01 1.248952e-04 3.049495e-01 9.614210e-01
#> [41] 2.098110e-01 4.683061e-01 1.397002e-01 8.323517e-01 3.280650e-01
#> [46] 5.843989e-01 1.477829e-01 7.356976e-02 9.238287e-01 3.280650e-01
#> [51] 7.356976e-02 7.792089e-01 1.464981e-02 5.996993e-01 1.100457e-01
#> [56] 2.508302e-01 5.892572e-02 5.255014e-01 6.977449e-03 6.949795e-01
#> [61] 3.140152e-02 3.641023e-01 1.043518e-02 4.142589e-01 4.965034e-01
#> [66] 6.464084e-01 7.792089e-01 3.140152e-02 4.276664e-01 2.401537e-01
#> [71] 3.049495e-01 1.244036e-02 1.910065e-01 6.306223e-01 1.729214e-01
#> [76] 5.255014e-01 6.464084e-01 9.238287e-01 5.892572e-02 3.140152e-02
#> [81] 9.055312e-02 9.614210e-01 1.702234e-05 2.045199e-03 3.140152e-02
#> [86] 2.935282e-01 5.421571e-03 9.049944e-01 5.109322e-01 8.682479e-01
#> [91] 6.785534e-01 5.692958e-01 2.098110e-01 1.560432e-01 6.270969e-04
#> [96] 5.425486e-02 1.910065e-01 4.982003e-02 9.689480e-02 7.115851e-01
#> [101] 1.945116e-02 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 92 96 157 88 128 180 170 96.1 177 139 192 171 145
#> 22.92 14.54 15.10 18.37 20.35 14.82 19.54 14.54 12.53 21.49 16.44 16.57 10.07
#> 51 164 180.1 10 197 51.1 51.2 15 86 139.1 192.1 81 55
#> 18.23 23.60 14.82 10.53 21.60 18.23 18.23 22.68 23.81 21.49 16.44 14.06 19.34
#> 129 136 117 180.2 5 101 10.1 10.2 184 123 183 86.1 18
#> 23.41 21.83 17.46 14.82 16.43 9.97 10.53 10.53 17.77 13.00 9.24 23.81 15.21
#> 127 23 81.1 40 101.1 157.1 140 134 55.1 70 157.2 55.2 52
#> 3.53 16.92 14.06 18.00 9.97 15.10 12.68 17.81 19.34 7.38 15.10 19.34 10.42
#> 136.1 154 108 192.2 170.1 123.1 63 107 99 180.3 169 133 60
#> 21.83 12.63 18.29 16.44 19.54 13.00 22.77 11.18 21.19 14.82 22.41 14.65 13.15
#> 56 52.1 36 96.2 181 18.1 66 111 37 110 123.2 56.1 70.1
#> 12.21 10.42 21.19 14.54 16.46 15.21 22.13 17.45 12.52 17.56 13.00 12.21 7.38
#> 170.2 36.1 97 127.1 78 129.1 99.1 125 113 16 155 183.1 49
#> 19.54 21.19 19.14 3.53 23.88 23.41 21.19 15.65 22.86 8.71 13.08 9.24 12.19
#> 14 23.1 184.1 168 105 111.1 150 88.1 159 197.1 119 112 147
#> 12.89 16.92 17.77 23.72 19.75 17.45 20.33 18.37 10.55 21.60 24.00 24.00 24.00
#> 94 47 1 196 35 17 131 126 48 103 3 46 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 9 80 172 17.1 12 193 71 71.1 65 72 34 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 132 67 119.1 22 65.1 191 20 33 2 185 160 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 102 35.1 44 74 34.1 143 1.1 191.1 151 185.1 131.1 191.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.1 186 148 75 38 54 65.2 120.1 35.2 160.1 19 75.1 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 80.2 147.1 103.1 162 193.1 103.2 152 120.2 67.1 83 102.1 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 48.2 182 2.1 20.1 72.1 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[28]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001332944 0.710315280 0.529361704
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.880075333 0.006593237 0.639718710
#> grade_iii, Cure model
#> 1.507112028
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 66 22.13 1 53 0 0
#> 59 10.16 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 30 17.43 1 78 0 0
#> 92 22.92 1 47 0 1
#> 111 17.45 1 47 0 1
#> 113 22.86 1 34 0 0
#> 78 23.88 1 43 0 0
#> 199 19.81 1 NA 0 1
#> 24 23.89 1 38 0 0
#> 79 16.23 1 54 1 0
#> 124 9.73 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 139 21.49 1 63 1 0
#> 91 5.33 1 61 0 1
#> 154 12.63 1 20 1 0
#> 158 20.14 1 74 1 0
#> 68 20.62 1 44 0 0
#> 199.1 19.81 1 NA 0 1
#> 157 15.10 1 47 0 0
#> 124.1 9.73 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 29 15.45 1 68 1 0
#> 105 19.75 1 60 0 0
#> 16 8.71 1 71 0 1
#> 189 10.51 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 18 15.21 1 49 1 0
#> 90 20.94 1 50 0 1
#> 63 22.77 1 31 1 0
#> 63.1 22.77 1 31 1 0
#> 92.1 22.92 1 47 0 1
#> 127 3.53 1 62 0 1
#> 167 15.55 1 56 1 0
#> 6 15.64 1 39 0 0
#> 8 18.43 1 32 0 0
#> 139.1 21.49 1 63 1 0
#> 63.2 22.77 1 31 1 0
#> 197 21.60 1 69 1 0
#> 123 13.00 1 44 1 0
#> 113.1 22.86 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 100 16.07 1 60 0 0
#> 195.1 11.76 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 42 12.43 1 49 0 1
#> 164.1 23.60 1 76 0 1
#> 58 19.34 1 39 0 0
#> 158.1 20.14 1 74 1 0
#> 86 23.81 1 58 0 1
#> 45 17.42 1 54 0 1
#> 108 18.29 1 39 0 1
#> 43 12.10 1 61 0 1
#> 99 21.19 1 38 0 1
#> 108.1 18.29 1 39 0 1
#> 164.2 23.60 1 76 0 1
#> 42.1 12.43 1 49 0 1
#> 32 20.90 1 37 1 0
#> 197.1 21.60 1 69 1 0
#> 127.1 3.53 1 62 0 1
#> 96.1 14.54 1 33 0 1
#> 5.1 16.43 1 51 0 1
#> 91.1 5.33 1 61 0 1
#> 181 16.46 1 45 0 1
#> 89 11.44 1 NA 0 0
#> 195.2 11.76 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 45.1 17.42 1 54 0 1
#> 68.1 20.62 1 44 0 0
#> 127.2 3.53 1 62 0 1
#> 105.1 19.75 1 60 0 0
#> 175 21.91 1 43 0 0
#> 4 17.64 1 NA 0 1
#> 51 18.23 1 83 0 1
#> 117 17.46 1 26 0 1
#> 6.1 15.64 1 39 0 0
#> 50 10.02 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 154.1 12.63 1 20 1 0
#> 41 18.02 1 40 1 0
#> 90.1 20.94 1 50 0 1
#> 97 19.14 1 65 0 1
#> 194 22.40 1 38 0 1
#> 4.1 17.64 1 NA 0 1
#> 184 17.77 1 38 0 0
#> 128 20.35 1 35 0 1
#> 114 13.68 1 NA 0 0
#> 89.1 11.44 1 NA 0 0
#> 133 14.65 1 57 0 0
#> 108.2 18.29 1 39 0 1
#> 145 10.07 1 65 1 0
#> 24.1 23.89 1 38 0 0
#> 139.2 21.49 1 63 1 0
#> 130 16.47 1 53 0 1
#> 51.1 18.23 1 83 0 1
#> 70 7.38 1 30 1 0
#> 78.1 23.88 1 43 0 0
#> 155 13.08 1 26 0 0
#> 40.1 18.00 1 28 1 0
#> 16.1 8.71 1 71 0 1
#> 49 12.19 1 48 1 0
#> 101 9.97 1 10 0 1
#> 168 23.72 1 70 0 0
#> 4.2 17.64 1 NA 0 1
#> 86.1 23.81 1 58 0 1
#> 194.1 22.40 1 38 0 1
#> 129 23.41 1 53 1 0
#> 177 12.53 1 75 0 0
#> 145.1 10.07 1 65 1 0
#> 29.1 15.45 1 68 1 0
#> 15 22.68 1 48 0 0
#> 80 24.00 0 41 0 0
#> 53 24.00 0 32 0 1
#> 82 24.00 0 34 0 0
#> 94 24.00 0 51 0 1
#> 148 24.00 0 61 1 0
#> 19 24.00 0 57 0 1
#> 135 24.00 0 58 1 0
#> 143 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 64 24.00 0 43 0 0
#> 46 24.00 0 71 0 0
#> 82.1 24.00 0 34 0 0
#> 122 24.00 0 66 0 0
#> 19.1 24.00 0 57 0 1
#> 71 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 46.1 24.00 0 71 0 0
#> 132 24.00 0 55 0 0
#> 147 24.00 0 76 1 0
#> 48 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 71.1 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 38 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 119 24.00 0 17 0 0
#> 35 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 116 24.00 0 58 0 1
#> 62 24.00 0 71 0 0
#> 142.1 24.00 0 53 0 0
#> 141 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 9 24.00 0 31 1 0
#> 119.1 24.00 0 17 0 0
#> 2.1 24.00 0 9 0 0
#> 161 24.00 0 45 0 0
#> 151 24.00 0 42 0 0
#> 120 24.00 0 68 0 1
#> 126 24.00 0 48 0 0
#> 172 24.00 0 41 0 0
#> 119.2 24.00 0 17 0 0
#> 12 24.00 0 63 0 0
#> 38.1 24.00 0 31 1 0
#> 142.2 24.00 0 53 0 0
#> 135.1 24.00 0 58 1 0
#> 72 24.00 0 40 0 1
#> 75 24.00 0 21 1 0
#> 12.1 24.00 0 63 0 0
#> 163 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 137 24.00 0 45 1 0
#> 84 24.00 0 39 0 1
#> 131 24.00 0 66 0 0
#> 109.1 24.00 0 48 0 0
#> 11 24.00 0 42 0 1
#> 20 24.00 0 46 1 0
#> 75.1 24.00 0 21 1 0
#> 67 24.00 0 25 0 0
#> 119.3 24.00 0 17 0 0
#> 65 24.00 0 57 1 0
#> 174 24.00 0 49 1 0
#> 38.2 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 172.1 24.00 0 41 0 0
#> 118 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 94.1 24.00 0 51 0 1
#> 122.1 24.00 0 66 0 0
#> 116.1 24.00 0 58 0 1
#> 200 24.00 0 64 0 0
#> 104 24.00 0 50 1 0
#> 80.1 24.00 0 41 0 0
#> 103 24.00 0 56 1 0
#> 143.1 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 132.1 24.00 0 55 0 0
#> 121 24.00 0 57 1 0
#> 161.1 24.00 0 45 0 0
#> 84.1 24.00 0 39 0 1
#> 198.1 24.00 0 66 0 1
#> 118.1 24.00 0 44 1 0
#> 161.2 24.00 0 45 0 0
#> 62.1 24.00 0 71 0 0
#> 46.2 24.00 0 71 0 0
#> 7 24.00 0 37 1 0
#> 137.1 24.00 0 45 1 0
#> 53.1 24.00 0 32 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.880 NA NA NA
#> 2 age, Cure model 0.00659 NA NA NA
#> 3 grade_ii, Cure model 0.640 NA NA NA
#> 4 grade_iii, Cure model 1.51 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00133 NA NA NA
#> 2 grade_ii, Survival model 0.710 NA NA NA
#> 3 grade_iii, Survival model 0.529 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.880075 0.006593 0.639719 1.507112
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 253.2
#> Residual Deviance: 235.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.880075333 0.006593237 0.639718710 1.507112028
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001332944 0.710315280 0.529361704
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.37255135 0.76353142 0.68966918 0.24707906 0.68121266 0.27424323
#> [7] 0.06620095 0.02312093 0.74742732 0.95872927 0.41838609 0.96572866
#> [13] 0.86442557 0.51865811 0.48928095 0.81854668 0.17010161 0.79533297
#> [19] 0.53743803 0.93753787 0.55626860 0.81082862 0.45947292 0.30152928
#> [25] 0.30152928 0.24707906 0.97956375 0.78741396 0.77151427 0.58439814
#> [31] 0.41838609 0.30152928 0.39619362 0.85684663 0.27424323 0.73126183
#> [37] 0.75547607 0.83399693 0.88671909 0.17010161 0.56566814 0.51865811
#> [43] 0.11221603 0.69813596 0.59372689 0.90875132 0.44913009 0.59372689
#> [49] 0.17010161 0.88671909 0.47940398 0.39619362 0.97956375 0.83399693
#> [55] 0.73126183 0.96572866 0.72302660 0.64704802 0.69813596 0.48928095
#> [61] 0.97956375 0.53743803 0.38436235 0.62051557 0.67269323 0.77151427
#> [67] 0.23209538 0.86442557 0.63823856 0.45947292 0.57507560 0.34935322
#> [73] 0.66410419 0.50888022 0.82626916 0.59372689 0.91604595 0.02312093
#> [79] 0.41838609 0.71473480 0.62051557 0.95168129 0.06620095 0.84920560
#> [85] 0.64704802 0.93753787 0.90142344 0.93038028 0.14974091 0.11221603
#> [91] 0.34935322 0.21646425 0.87926287 0.91604595 0.79533297 0.33704484
#> [97] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 66 125 30 92 111 113 78 24 79 25 139 91 154
#> 22.13 15.65 17.43 22.92 17.45 22.86 23.88 23.89 16.23 6.32 21.49 5.33 12.63
#> 158 68 157 164 29 105 16 170 18 90 63 63.1 92.1
#> 20.14 20.62 15.10 23.60 15.45 19.75 8.71 19.54 15.21 20.94 22.77 22.77 22.92
#> 127 167 6 8 139.1 63.2 197 123 113.1 5 100 96 42
#> 3.53 15.55 15.64 18.43 21.49 22.77 21.60 13.00 22.86 16.43 16.07 14.54 12.43
#> 164.1 58 158.1 86 45 108 43 99 108.1 164.2 42.1 32 197.1
#> 23.60 19.34 20.14 23.81 17.42 18.29 12.10 21.19 18.29 23.60 12.43 20.90 21.60
#> 127.1 96.1 5.1 91.1 181 40 45.1 68.1 127.2 105.1 175 51 117
#> 3.53 14.54 16.43 5.33 16.46 18.00 17.42 20.62 3.53 19.75 21.91 18.23 17.46
#> 6.1 69 154.1 41 90.1 97 194 184 128 133 108.2 145 24.1
#> 15.64 23.23 12.63 18.02 20.94 19.14 22.40 17.77 20.35 14.65 18.29 10.07 23.89
#> 139.2 130 51.1 70 78.1 155 40.1 16.1 49 101 168 86.1 194.1
#> 21.49 16.47 18.23 7.38 23.88 13.08 18.00 8.71 12.19 9.97 23.72 23.81 22.40
#> 129 177 145.1 29.1 15 80 53 82 94 148 19 135 143
#> 23.41 12.53 10.07 15.45 22.68 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 64 46 82.1 122 19.1 71 2 46.1 132 147 48 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.1 44 38 109 119 35 116 62 142.1 141 198 9 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.1 161 151 120 126 172 119.2 12 38.1 142.2 135.1 72 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.1 163 95 137 84 131 109.1 11 20 75.1 67 119.3 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 38.2 54 172.1 118 98 94.1 122.1 116.1 200 104 80.1 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.1 22 132.1 121 161.1 84.1 198.1 118.1 161.2 62.1 46.2 7 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[29]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.009354476 0.569397665 0.461095152
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.441006574 0.001028824 0.322122187
#> grade_iii, Cure model
#> 1.417322779
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 179 18.63 1 42 0 0
#> 88 18.37 1 47 0 0
#> 93 10.33 1 52 0 1
#> 14 12.89 1 21 0 0
#> 190 20.81 1 42 1 0
#> 85 16.44 1 36 0 0
#> 41 18.02 1 40 1 0
#> 110 17.56 1 65 0 1
#> 13 14.34 1 54 0 1
#> 96 14.54 1 33 0 1
#> 169 22.41 1 46 0 0
#> 32 20.90 1 37 1 0
#> 92 22.92 1 47 0 1
#> 113 22.86 1 34 0 0
#> 111 17.45 1 47 0 1
#> 199 19.81 1 NA 0 1
#> 188 16.16 1 46 0 1
#> 77 7.27 1 67 0 1
#> 23 16.92 1 61 0 0
#> 89 11.44 1 NA 0 0
#> 36 21.19 1 48 0 1
#> 45 17.42 1 54 0 1
#> 111.1 17.45 1 47 0 1
#> 130 16.47 1 53 0 1
#> 61 10.12 1 36 0 1
#> 24 23.89 1 38 0 0
#> 183 9.24 1 67 1 0
#> 16 8.71 1 71 0 1
#> 24.1 23.89 1 38 0 0
#> 56 12.21 1 60 0 0
#> 76 19.22 1 54 0 1
#> 51 18.23 1 83 0 1
#> 181 16.46 1 45 0 1
#> 168 23.72 1 70 0 0
#> 149 8.37 1 33 1 0
#> 183.1 9.24 1 67 1 0
#> 69 23.23 1 25 0 1
#> 14.1 12.89 1 21 0 0
#> 49 12.19 1 48 1 0
#> 93.1 10.33 1 52 0 1
#> 88.1 18.37 1 47 0 0
#> 45.1 17.42 1 54 0 1
#> 127 3.53 1 62 0 1
#> 66 22.13 1 53 0 0
#> 88.2 18.37 1 47 0 0
#> 60 13.15 1 38 1 0
#> 101 9.97 1 10 0 1
#> 68 20.62 1 44 0 0
#> 93.2 10.33 1 52 0 1
#> 39 15.59 1 37 0 1
#> 86 23.81 1 58 0 1
#> 85.1 16.44 1 36 0 0
#> 36.1 21.19 1 48 0 1
#> 68.1 20.62 1 44 0 0
#> 32.1 20.90 1 37 1 0
#> 157 15.10 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 181.1 16.46 1 45 0 1
#> 180 14.82 1 37 0 0
#> 101.1 9.97 1 10 0 1
#> 171 16.57 1 41 0 1
#> 42 12.43 1 49 0 1
#> 117 17.46 1 26 0 1
#> 13.1 14.34 1 54 0 1
#> 40 18.00 1 28 1 0
#> 76.1 19.22 1 54 0 1
#> 106 16.67 1 49 1 0
#> 16.1 8.71 1 71 0 1
#> 70 7.38 1 30 1 0
#> 18 15.21 1 49 1 0
#> 110.1 17.56 1 65 0 1
#> 145 10.07 1 65 1 0
#> 128 20.35 1 35 0 1
#> 32.2 20.90 1 37 1 0
#> 63 22.77 1 31 1 0
#> 63.1 22.77 1 31 1 0
#> 5 16.43 1 51 0 1
#> 136 21.83 1 43 0 1
#> 39.1 15.59 1 37 0 1
#> 195 11.76 1 NA 1 0
#> 136.1 21.83 1 43 0 1
#> 130.1 16.47 1 53 0 1
#> 68.2 20.62 1 44 0 0
#> 86.1 23.81 1 58 0 1
#> 85.2 16.44 1 36 0 0
#> 159 10.55 1 50 0 1
#> 61.1 10.12 1 36 0 1
#> 52.1 10.42 1 52 0 1
#> 197 21.60 1 69 1 0
#> 166 19.98 1 48 0 0
#> 91 5.33 1 61 0 1
#> 63.2 22.77 1 31 1 0
#> 145.1 10.07 1 65 1 0
#> 25 6.32 1 34 1 0
#> 155 13.08 1 26 0 0
#> 66.1 22.13 1 53 0 0
#> 140 12.68 1 59 1 0
#> 177 12.53 1 75 0 0
#> 183.2 9.24 1 67 1 0
#> 41.1 18.02 1 40 1 0
#> 114 13.68 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 6 15.64 1 39 0 0
#> 25.1 6.32 1 34 1 0
#> 108 18.29 1 39 0 1
#> 170 19.54 1 43 0 1
#> 130.2 16.47 1 53 0 1
#> 59 10.16 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 52.2 10.42 1 52 0 1
#> 170.1 19.54 1 43 0 1
#> 151 24.00 0 42 0 0
#> 156 24.00 0 50 1 0
#> 1 24.00 0 23 1 0
#> 121 24.00 0 57 1 0
#> 132 24.00 0 55 0 0
#> 64 24.00 0 43 0 0
#> 34 24.00 0 36 0 0
#> 118 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 46 24.00 0 71 0 0
#> 138 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 200 24.00 0 64 0 0
#> 163 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 12 24.00 0 63 0 0
#> 75 24.00 0 21 1 0
#> 196 24.00 0 19 0 0
#> 95 24.00 0 68 0 1
#> 185.1 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 44 24.00 0 56 0 0
#> 161 24.00 0 45 0 0
#> 46.1 24.00 0 71 0 0
#> 172 24.00 0 41 0 0
#> 146 24.00 0 63 1 0
#> 137 24.00 0 45 1 0
#> 142.1 24.00 0 53 0 0
#> 67.1 24.00 0 25 0 0
#> 200.1 24.00 0 64 0 0
#> 98 24.00 0 34 1 0
#> 65 24.00 0 57 1 0
#> 72 24.00 0 40 0 1
#> 72.1 24.00 0 40 0 1
#> 53 24.00 0 32 0 1
#> 48.1 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 75.1 24.00 0 21 1 0
#> 84 24.00 0 39 0 1
#> 62 24.00 0 71 0 0
#> 143 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 48.2 24.00 0 31 1 0
#> 34.1 24.00 0 36 0 0
#> 87 24.00 0 27 0 0
#> 185.2 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#> 109 24.00 0 48 0 0
#> 33 24.00 0 53 0 0
#> 200.2 24.00 0 64 0 0
#> 173 24.00 0 19 0 1
#> 84.1 24.00 0 39 0 1
#> 98.1 24.00 0 34 1 0
#> 193 24.00 0 45 0 1
#> 11 24.00 0 42 0 1
#> 156.1 24.00 0 50 1 0
#> 34.2 24.00 0 36 0 0
#> 115 24.00 0 NA 1 0
#> 120 24.00 0 68 0 1
#> 109.1 24.00 0 48 0 0
#> 191 24.00 0 60 0 1
#> 198 24.00 0 66 0 1
#> 131.1 24.00 0 66 0 0
#> 87.1 24.00 0 27 0 0
#> 172.1 24.00 0 41 0 0
#> 121.1 24.00 0 57 1 0
#> 200.3 24.00 0 64 0 0
#> 143.1 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 3 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 146.1 24.00 0 63 1 0
#> 1.1 24.00 0 23 1 0
#> 131.2 24.00 0 66 0 0
#> 9.1 24.00 0 31 1 0
#> 95.2 24.00 0 68 0 1
#> 137.1 24.00 0 45 1 0
#> 196.1 24.00 0 19 0 0
#> 46.2 24.00 0 71 0 0
#> 193.1 24.00 0 45 0 1
#> 17 24.00 0 38 0 1
#> 161.1 24.00 0 45 0 0
#> 47.1 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.441 NA NA NA
#> 2 age, Cure model 0.00103 NA NA NA
#> 3 grade_ii, Cure model 0.322 NA NA NA
#> 4 grade_iii, Cure model 1.42 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00935 NA NA NA
#> 2 grade_ii, Survival model 0.569 NA NA NA
#> 3 grade_iii, Survival model 0.461 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.441007 0.001029 0.322122 1.417323
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 248.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.441006574 0.001028824 0.322122187 1.417322779
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.009354476 0.569397665 0.461095152
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.59599208 0.60411609 0.90838749 0.84833220 0.49719736 0.76000316
#> [7] 0.64304856 0.66481054 0.82726995 0.82185527 0.36420012 0.46740821
#> [13] 0.28088078 0.30065316 0.68543947 0.78301878 0.97942966 0.71154397
#> [19] 0.44518781 0.69869015 0.68543947 0.73050390 0.92233944 0.09156089
#> [25] 0.94950933 0.96247706 0.09156089 0.87413622 0.57113209 0.63546090
#> [31] 0.74833293 0.23474905 0.97098241 0.94950933 0.25884294 0.84833220
#> [37] 0.87920025 0.90838749 0.60411609 0.69869015 0.99593548 0.37924926
#> [43] 0.60411609 0.83783935 0.94056177 0.50700875 0.90838749 0.79435393
#> [49] 0.18453666 0.76000316 0.44518781 0.50700875 0.46740821 0.81092744
#> [55] 0.89408871 0.74833293 0.81639892 0.94056177 0.72426572 0.86905000
#> [61] 0.67858727 0.82726995 0.65759875 0.57113209 0.71795542 0.96247706
#> [67] 0.97521829 0.80543551 0.66481054 0.93155067 0.53506418 0.46740821
#> [73] 0.31995095 0.31995095 0.77728242 0.40734925 0.79435393 0.40734925
#> [79] 0.73050390 0.50700875 0.18453666 0.76000316 0.88917196 0.92233944
#> [85] 0.89408871 0.43302260 0.54438535 0.99184034 0.31995095 0.93155067
#> [91] 0.98360570 0.84309027 0.37924926 0.85875580 0.86391849 0.94950933
#> [97] 0.64304856 0.58781444 0.78869532 0.98360570 0.62764487 0.55361693
#> [103] 0.73050390 0.88421321 0.89408871 0.55361693 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 179 88 93 14 190 85 41 110 13 96 169 32 92
#> 18.63 18.37 10.33 12.89 20.81 16.44 18.02 17.56 14.34 14.54 22.41 20.90 22.92
#> 113 111 188 77 23 36 45 111.1 130 61 24 183 16
#> 22.86 17.45 16.16 7.27 16.92 21.19 17.42 17.45 16.47 10.12 23.89 9.24 8.71
#> 24.1 56 76 51 181 168 149 183.1 69 14.1 49 93.1 88.1
#> 23.89 12.21 19.22 18.23 16.46 23.72 8.37 9.24 23.23 12.89 12.19 10.33 18.37
#> 45.1 127 66 88.2 60 101 68 93.2 39 86 85.1 36.1 68.1
#> 17.42 3.53 22.13 18.37 13.15 9.97 20.62 10.33 15.59 23.81 16.44 21.19 20.62
#> 32.1 157 52 181.1 180 101.1 171 42 117 13.1 40 76.1 106
#> 20.90 15.10 10.42 16.46 14.82 9.97 16.57 12.43 17.46 14.34 18.00 19.22 16.67
#> 16.1 70 18 110.1 145 128 32.2 63 63.1 5 136 39.1 136.1
#> 8.71 7.38 15.21 17.56 10.07 20.35 20.90 22.77 22.77 16.43 21.83 15.59 21.83
#> 130.1 68.2 86.1 85.2 159 61.1 52.1 197 166 91 63.2 145.1 25
#> 16.47 20.62 23.81 16.44 10.55 10.12 10.42 21.60 19.98 5.33 22.77 10.07 6.32
#> 155 66.1 140 177 183.2 41.1 97 6 25.1 108 170 130.2 107
#> 13.08 22.13 12.68 12.53 9.24 18.02 19.14 15.64 6.32 18.29 19.54 16.47 11.18
#> 52.2 170.1 151 156 1 121 132 64 34 118 48 142 46
#> 10.42 19.54 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 67 200 163 185 148 12 75 196 95 185.1 152 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 161 46.1 172 146 137 142.1 67.1 200.1 98 65 72 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 48.1 102 75.1 84 62 143 83 48.2 34.1 87 185.2 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 95.1 109 33 200.2 173 84.1 98.1 193 11 156.1 34.2 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.1 191 198 131.1 87.1 172.1 121.1 200.3 143.1 47 3 135 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 131.2 9.1 95.2 137.1 196.1 46.2 193.1 17 161.1 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[30]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003924558 0.784724501 0.696789079
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.446804017 0.013782931 -0.093638554
#> grade_iii, Cure model
#> -0.004114069
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 8 18.43 1 32 0 0
#> 157 15.10 1 47 0 0
#> 13 14.34 1 54 0 1
#> 145 10.07 1 65 1 0
#> 179 18.63 1 42 0 0
#> 100 16.07 1 60 0 0
#> 187 9.92 1 39 1 0
#> 123 13.00 1 44 1 0
#> 51 18.23 1 83 0 1
#> 69 23.23 1 25 0 1
#> 6 15.64 1 39 0 0
#> 167 15.55 1 56 1 0
#> 66 22.13 1 53 0 0
#> 58 19.34 1 39 0 0
#> 66.1 22.13 1 53 0 0
#> 170 19.54 1 43 0 1
#> 76 19.22 1 54 0 1
#> 23 16.92 1 61 0 0
#> 59 10.16 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 192 16.44 1 31 1 0
#> 85 16.44 1 36 0 0
#> 127 3.53 1 62 0 1
#> 92 22.92 1 47 0 1
#> 88 18.37 1 47 0 0
#> 153 21.33 1 55 1 0
#> 117 17.46 1 26 0 1
#> 51.1 18.23 1 83 0 1
#> 40 18.00 1 28 1 0
#> 197 21.60 1 69 1 0
#> 175 21.91 1 43 0 0
#> 107 11.18 1 54 1 0
#> 24 23.89 1 38 0 0
#> 58.1 19.34 1 39 0 0
#> 155 13.08 1 26 0 0
#> 114 13.68 1 NA 0 0
#> 88.1 18.37 1 47 0 0
#> 199 19.81 1 NA 0 1
#> 89 11.44 1 NA 0 0
#> 106 16.67 1 49 1 0
#> 133.1 14.65 1 57 0 0
#> 97 19.14 1 65 0 1
#> 106.1 16.67 1 49 1 0
#> 78 23.88 1 43 0 0
#> 124 9.73 1 NA 1 0
#> 76.1 19.22 1 54 0 1
#> 24.1 23.89 1 38 0 0
#> 78.1 23.88 1 43 0 0
#> 188 16.16 1 46 0 1
#> 43 12.10 1 61 0 1
#> 170.1 19.54 1 43 0 1
#> 166 19.98 1 48 0 0
#> 164 23.60 1 76 0 1
#> 129 23.41 1 53 1 0
#> 117.1 17.46 1 26 0 1
#> 108 18.29 1 39 0 1
#> 199.1 19.81 1 NA 0 1
#> 168 23.72 1 70 0 0
#> 24.2 23.89 1 38 0 0
#> 154 12.63 1 20 1 0
#> 168.1 23.72 1 70 0 0
#> 18 15.21 1 49 1 0
#> 63 22.77 1 31 1 0
#> 153.1 21.33 1 55 1 0
#> 66.2 22.13 1 53 0 0
#> 36 21.19 1 48 0 1
#> 39 15.59 1 37 0 1
#> 16 8.71 1 71 0 1
#> 139 21.49 1 63 1 0
#> 110 17.56 1 65 0 1
#> 117.2 17.46 1 26 0 1
#> 188.1 16.16 1 46 0 1
#> 127.1 3.53 1 62 0 1
#> 184 17.77 1 38 0 0
#> 89.1 11.44 1 NA 0 0
#> 4 17.64 1 NA 0 1
#> 86 23.81 1 58 0 1
#> 85.1 16.44 1 36 0 0
#> 154.1 12.63 1 20 1 0
#> 49 12.19 1 48 1 0
#> 29 15.45 1 68 1 0
#> 37 12.52 1 57 1 0
#> 168.2 23.72 1 70 0 0
#> 49.1 12.19 1 48 1 0
#> 18.1 15.21 1 49 1 0
#> 158 20.14 1 74 1 0
#> 149 8.37 1 33 1 0
#> 180 14.82 1 37 0 0
#> 70 7.38 1 30 1 0
#> 37.1 12.52 1 57 1 0
#> 129.1 23.41 1 53 1 0
#> 150 20.33 1 48 0 0
#> 15 22.68 1 48 0 0
#> 76.2 19.22 1 54 0 1
#> 15.1 22.68 1 48 0 0
#> 40.1 18.00 1 28 1 0
#> 91 5.33 1 61 0 1
#> 23.1 16.92 1 61 0 0
#> 190 20.81 1 42 1 0
#> 42 12.43 1 49 0 1
#> 181 16.46 1 45 0 1
#> 26 15.77 1 49 0 1
#> 15.2 22.68 1 48 0 0
#> 108.1 18.29 1 39 0 1
#> 129.2 23.41 1 53 1 0
#> 16.1 8.71 1 71 0 1
#> 63.1 22.77 1 31 1 0
#> 170.2 19.54 1 43 0 1
#> 6.1 15.64 1 39 0 0
#> 149.1 8.37 1 33 1 0
#> 123.1 13.00 1 44 1 0
#> 108.2 18.29 1 39 0 1
#> 34 24.00 0 36 0 0
#> 2 24.00 0 9 0 0
#> 104 24.00 0 50 1 0
#> 82 24.00 0 34 0 0
#> 80 24.00 0 41 0 0
#> 173 24.00 0 19 0 1
#> 71 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 156 24.00 0 50 1 0
#> 94 24.00 0 51 0 1
#> 118 24.00 0 44 1 0
#> 104.1 24.00 0 50 1 0
#> 80.1 24.00 0 41 0 0
#> 176 24.00 0 43 0 1
#> 118.1 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 28 24.00 0 67 1 0
#> 146 24.00 0 63 1 0
#> 74.1 24.00 0 43 0 1
#> 165 24.00 0 47 0 0
#> 185 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 53 24.00 0 32 0 1
#> 67 24.00 0 25 0 0
#> 67.1 24.00 0 25 0 0
#> 98.1 24.00 0 34 1 0
#> 137.1 24.00 0 45 1 0
#> 198 24.00 0 66 0 1
#> 95 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 196 24.00 0 19 0 0
#> 83 24.00 0 6 0 0
#> 196.1 24.00 0 19 0 0
#> 144 24.00 0 28 0 1
#> 200.1 24.00 0 64 0 0
#> 102 24.00 0 49 0 0
#> 147 24.00 0 76 1 0
#> 122 24.00 0 66 0 0
#> 147.1 24.00 0 76 1 0
#> 11 24.00 0 42 0 1
#> 176.1 24.00 0 43 0 1
#> 44 24.00 0 56 0 0
#> 173.1 24.00 0 19 0 1
#> 148 24.00 0 61 1 0
#> 47 24.00 0 38 0 1
#> 47.1 24.00 0 38 0 1
#> 131 24.00 0 66 0 0
#> 148.1 24.00 0 61 1 0
#> 144.1 24.00 0 28 0 1
#> 20 24.00 0 46 1 0
#> 19 24.00 0 57 0 1
#> 104.2 24.00 0 50 1 0
#> 94.1 24.00 0 51 0 1
#> 176.2 24.00 0 43 0 1
#> 65 24.00 0 57 1 0
#> 176.3 24.00 0 43 0 1
#> 17 24.00 0 38 0 1
#> 31 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 17.1 24.00 0 38 0 1
#> 71.1 24.00 0 51 0 0
#> 3.1 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 104.3 24.00 0 50 1 0
#> 176.4 24.00 0 43 0 1
#> 34.1 24.00 0 36 0 0
#> 65.1 24.00 0 57 1 0
#> 72 24.00 0 40 0 1
#> 74.2 24.00 0 43 0 1
#> 22 24.00 0 52 1 0
#> 44.1 24.00 0 56 0 0
#> 121 24.00 0 57 1 0
#> 11.1 24.00 0 42 0 1
#> 165.1 24.00 0 47 0 0
#> 35 24.00 0 51 0 0
#> 80.2 24.00 0 41 0 0
#> 3.2 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#> 20.1 24.00 0 46 1 0
#> 64 24.00 0 43 0 0
#> 12 24.00 0 63 0 0
#> 1 24.00 0 23 1 0
#> 173.2 24.00 0 19 0 1
#> 102.1 24.00 0 49 0 0
#> 147.2 24.00 0 76 1 0
#> 162 24.00 0 51 0 0
#> 28.1 24.00 0 67 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.447 NA NA NA
#> 2 age, Cure model 0.0138 NA NA NA
#> 3 grade_ii, Cure model -0.0936 NA NA NA
#> 4 grade_iii, Cure model -0.00411 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00392 NA NA NA
#> 2 grade_ii, Survival model 0.785 NA NA NA
#> 3 grade_iii, Survival model 0.697 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.446804 0.013783 -0.093639 -0.004114
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 263 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.446804017 0.013782931 -0.093638554 -0.004114069
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003924558 0.784724501 0.696789079
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.52367980 0.80560328 0.83615917 0.93140234 0.51439991 0.73543591
#> [7] 0.93845384 0.85142449 0.57814404 0.20957001 0.75127908 0.77488763
#> [13] 0.28973799 0.45837786 0.28973799 0.42999813 0.47761245 0.65478282
#> [19] 0.82088358 0.69577161 0.69577161 0.98658017 0.22242180 0.53297914
#> [25] 0.35775476 0.63017698 0.57814404 0.59578488 0.33513587 0.32342666
#> [31] 0.92431335 0.01770770 0.45837786 0.84378848 0.53297914 0.67138032
#> [37] 0.82088358 0.50514540 0.67138032 0.05653315 0.47761245 0.01770770
#> [43] 0.05653315 0.71965887 0.91718208 0.42999813 0.41984565 0.15463983
#> [49] 0.17154022 0.63017698 0.55152368 0.10702711 0.01770770 0.86640227
#> [55] 0.10702711 0.79042915 0.23479546 0.35775476 0.28973799 0.37877184
#> [61] 0.76703066 0.94545898 0.34657659 0.62158987 0.63017698 0.71965887
#> [67] 0.98658017 0.61293638 0.09026913 0.69577161 0.86640227 0.90291089
#> [73] 0.78268456 0.88111894 0.10702711 0.90291089 0.79042915 0.40973516
#> [79] 0.95931121 0.81323858 0.97298075 0.88111894 0.17154022 0.39946263
#> [85] 0.25677258 0.47761245 0.25677258 0.59578488 0.97979414 0.65478282
#> [91] 0.38923526 0.89565296 0.68765267 0.74338519 0.25677258 0.55152368
#> [97] 0.17154022 0.94545898 0.23479546 0.42999813 0.75127908 0.95931121
#> [103] 0.85142449 0.55152368 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 8 157 13 145 179 100 187 123 51 69 6 167 66
#> 18.43 15.10 14.34 10.07 18.63 16.07 9.92 13.00 18.23 23.23 15.64 15.55 22.13
#> 58 66.1 170 76 23 133 192 85 127 92 88 153 117
#> 19.34 22.13 19.54 19.22 16.92 14.65 16.44 16.44 3.53 22.92 18.37 21.33 17.46
#> 51.1 40 197 175 107 24 58.1 155 88.1 106 133.1 97 106.1
#> 18.23 18.00 21.60 21.91 11.18 23.89 19.34 13.08 18.37 16.67 14.65 19.14 16.67
#> 78 76.1 24.1 78.1 188 43 170.1 166 164 129 117.1 108 168
#> 23.88 19.22 23.89 23.88 16.16 12.10 19.54 19.98 23.60 23.41 17.46 18.29 23.72
#> 24.2 154 168.1 18 63 153.1 66.2 36 39 16 139 110 117.2
#> 23.89 12.63 23.72 15.21 22.77 21.33 22.13 21.19 15.59 8.71 21.49 17.56 17.46
#> 188.1 127.1 184 86 85.1 154.1 49 29 37 168.2 49.1 18.1 158
#> 16.16 3.53 17.77 23.81 16.44 12.63 12.19 15.45 12.52 23.72 12.19 15.21 20.14
#> 149 180 70 37.1 129.1 150 15 76.2 15.1 40.1 91 23.1 190
#> 8.37 14.82 7.38 12.52 23.41 20.33 22.68 19.22 22.68 18.00 5.33 16.92 20.81
#> 42 181 26 15.2 108.1 129.2 16.1 63.1 170.2 6.1 149.1 123.1 108.2
#> 12.43 16.46 15.77 22.68 18.29 23.41 8.71 22.77 19.54 15.64 8.37 13.00 18.29
#> 34 2 104 82 80 173 71 74 156 94 118 104.1 80.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 118.1 98 28 146 74.1 165 185 137 53 67 67.1 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 198 95 200 196 83 196.1 144 200.1 102 147 122 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 176.1 44 173.1 148 47 47.1 131 148.1 144.1 20 19 104.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 176.2 65 176.3 17 31 3 17.1 71.1 3.1 163 132 104.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.4 34.1 65.1 72 74.2 22 44.1 121 11.1 165.1 35 80.2 3.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.1 20.1 64 12 1 173.2 102.1 147.2 162 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[31]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01382514 1.43309153 0.57402785
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.00028674 0.02199459 0.15565070
#> grade_iii, Cure model
#> 0.50708809
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 183 9.24 1 67 1 0
#> 123 13.00 1 44 1 0
#> 14 12.89 1 21 0 0
#> 177 12.53 1 75 0 0
#> 145 10.07 1 65 1 0
#> 171 16.57 1 41 0 1
#> 164 23.60 1 76 0 1
#> 50 10.02 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 85 16.44 1 36 0 0
#> 90 20.94 1 50 0 1
#> 155 13.08 1 26 0 0
#> 78 23.88 1 43 0 0
#> 78.1 23.88 1 43 0 0
#> 14.1 12.89 1 21 0 0
#> 59 10.16 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 130 16.47 1 53 0 1
#> 158 20.14 1 74 1 0
#> 187 9.92 1 39 1 0
#> 164.1 23.60 1 76 0 1
#> 30 17.43 1 78 0 0
#> 26 15.77 1 49 0 1
#> 25 6.32 1 34 1 0
#> 107 11.18 1 54 1 0
#> 49 12.19 1 48 1 0
#> 4 17.64 1 NA 0 1
#> 57 14.46 1 45 0 1
#> 167 15.55 1 56 1 0
#> 56 12.21 1 60 0 0
#> 78.2 23.88 1 43 0 0
#> 197 21.60 1 69 1 0
#> 175 21.91 1 43 0 0
#> 79 16.23 1 54 1 0
#> 24 23.89 1 38 0 0
#> 139 21.49 1 63 1 0
#> 169 22.41 1 46 0 0
#> 133 14.65 1 57 0 0
#> 107.1 11.18 1 54 1 0
#> 170 19.54 1 43 0 1
#> 105 19.75 1 60 0 0
#> 190 20.81 1 42 1 0
#> 168 23.72 1 70 0 0
#> 140 12.68 1 59 1 0
#> 153 21.33 1 55 1 0
#> 110 17.56 1 65 0 1
#> 99 21.19 1 38 0 1
#> 8 18.43 1 32 0 0
#> 177.1 12.53 1 75 0 0
#> 89 11.44 1 NA 0 0
#> 68 20.62 1 44 0 0
#> 154 12.63 1 20 1 0
#> 154.1 12.63 1 20 1 0
#> 66.1 22.13 1 53 0 0
#> 96 14.54 1 33 0 1
#> 169.1 22.41 1 46 0 0
#> 181 16.46 1 45 0 1
#> 153.1 21.33 1 55 1 0
#> 6 15.64 1 39 0 0
#> 168.1 23.72 1 70 0 0
#> 106 16.67 1 49 1 0
#> 8.1 18.43 1 32 0 0
#> 40 18.00 1 28 1 0
#> 59.1 10.16 1 NA 1 0
#> 170.1 19.54 1 43 0 1
#> 23 16.92 1 61 0 0
#> 51.1 18.23 1 83 0 1
#> 69 23.23 1 25 0 1
#> 93 10.33 1 52 0 1
#> 181.1 16.46 1 45 0 1
#> 66.2 22.13 1 53 0 0
#> 36 21.19 1 48 0 1
#> 108 18.29 1 39 0 1
#> 77 7.27 1 67 0 1
#> 37 12.52 1 57 1 0
#> 113 22.86 1 34 0 0
#> 58 19.34 1 39 0 0
#> 77.1 7.27 1 67 0 1
#> 110.1 17.56 1 65 0 1
#> 184 17.77 1 38 0 0
#> 164.2 23.60 1 76 0 1
#> 167.1 15.55 1 56 1 0
#> 97 19.14 1 65 0 1
#> 49.1 12.19 1 48 1 0
#> 86 23.81 1 58 0 1
#> 4.1 17.64 1 NA 0 1
#> 169.2 22.41 1 46 0 0
#> 149 8.37 1 33 1 0
#> 106.1 16.67 1 49 1 0
#> 175.1 21.91 1 43 0 0
#> 149.1 8.37 1 33 1 0
#> 78.3 23.88 1 43 0 0
#> 106.2 16.67 1 49 1 0
#> 49.2 12.19 1 48 1 0
#> 90.1 20.94 1 50 0 1
#> 52 10.42 1 52 0 1
#> 77.2 7.27 1 67 0 1
#> 79.1 16.23 1 54 1 0
#> 166 19.98 1 48 0 0
#> 81 14.06 1 34 0 0
#> 49.3 12.19 1 48 1 0
#> 5 16.43 1 51 0 1
#> 66.3 22.13 1 53 0 0
#> 136 21.83 1 43 0 1
#> 155.1 13.08 1 26 0 0
#> 86.1 23.81 1 58 0 1
#> 26.1 15.77 1 49 0 1
#> 52.1 10.42 1 52 0 1
#> 92 22.92 1 47 0 1
#> 25.1 6.32 1 34 1 0
#> 70 7.38 1 30 1 0
#> 130.1 16.47 1 53 0 1
#> 62 24.00 0 71 0 0
#> 73 24.00 0 NA 0 1
#> 53 24.00 0 32 0 1
#> 47 24.00 0 38 0 1
#> 34 24.00 0 36 0 0
#> 87 24.00 0 27 0 0
#> 83 24.00 0 6 0 0
#> 176 24.00 0 43 0 1
#> 118 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 109 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 83.1 24.00 0 6 0 0
#> 9.1 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 182 24.00 0 35 0 0
#> 162 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 83.2 24.00 0 6 0 0
#> 165 24.00 0 47 0 0
#> 118.1 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 28 24.00 0 67 1 0
#> 144 24.00 0 28 0 1
#> 116 24.00 0 58 0 1
#> 64 24.00 0 43 0 0
#> 12 24.00 0 63 0 0
#> 137 24.00 0 45 1 0
#> 131 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 34.1 24.00 0 36 0 0
#> 94 24.00 0 51 0 1
#> 87.1 24.00 0 27 0 0
#> 200.1 24.00 0 64 0 0
#> 53.1 24.00 0 32 0 1
#> 102 24.00 0 49 0 0
#> 3 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 160 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 22 24.00 0 52 1 0
#> 162.1 24.00 0 51 0 0
#> 73.1 24.00 0 NA 0 1
#> 12.1 24.00 0 63 0 0
#> 38 24.00 0 31 1 0
#> 87.2 24.00 0 27 0 0
#> 173.1 24.00 0 19 0 1
#> 17 24.00 0 38 0 1
#> 12.2 24.00 0 63 0 0
#> 75 24.00 0 21 1 0
#> 20 24.00 0 46 1 0
#> 28.1 24.00 0 67 1 0
#> 135 24.00 0 58 1 0
#> 65 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 143 24.00 0 51 0 0
#> 73.2 24.00 0 NA 0 1
#> 33 24.00 0 53 0 0
#> 2 24.00 0 9 0 0
#> 198 24.00 0 66 0 1
#> 144.1 24.00 0 28 0 1
#> 83.3 24.00 0 6 0 0
#> 12.3 24.00 0 63 0 0
#> 146 24.00 0 63 1 0
#> 27 24.00 0 63 1 0
#> 82 24.00 0 34 0 0
#> 160.1 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 54 24.00 0 53 1 0
#> 131.1 24.00 0 66 0 0
#> 83.4 24.00 0 6 0 0
#> 191 24.00 0 60 0 1
#> 135.1 24.00 0 58 1 0
#> 72 24.00 0 40 0 1
#> 19 24.00 0 57 0 1
#> 46 24.00 0 71 0 0
#> 152 24.00 0 36 0 1
#> 141.1 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 131.2 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 80 24.00 0 41 0 0
#> 28.2 24.00 0 67 1 0
#> 34.2 24.00 0 36 0 0
#> 173.2 24.00 0 19 0 1
#> 148.1 24.00 0 61 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.00 NA NA NA
#> 2 age, Cure model 0.0220 NA NA NA
#> 3 grade_ii, Cure model 0.156 NA NA NA
#> 4 grade_iii, Cure model 0.507 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0138 NA NA NA
#> 2 grade_ii, Survival model 1.43 NA NA NA
#> 3 grade_iii, Survival model 0.574 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00029 0.02199 0.15565 0.50709
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.5
#> Residual Deviance: 253.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00028674 0.02199459 0.15565070 0.50708809
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01382514 1.43309153 0.57402785
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9254731729 0.7315757347 0.7415677652 0.7902178841 0.9079445999
#> [6] 0.5282045762 0.0435134601 0.1209257020 0.5797993387 0.2649922073
#> [11] 0.7113770806 0.0044823216 0.0044823216 0.7415677652 0.4109923177
#> [16] 0.5385497978 0.3061696785 0.9167694046 0.0435134601 0.4756225828
#> [21] 0.6209496971 0.9838607452 0.8637855893 0.8282107467 0.6912612779
#> [26] 0.6514201648 0.8186884041 0.0044823216 0.2000543079 0.1632341963
#> [31] 0.6007997897 0.0008261998 0.2121524430 0.0929685502 0.6711947718
#> [36] 0.8637855893 0.3369386352 0.3265063978 0.2858085064 0.0295122566
#> [41] 0.7615520045 0.2237518926 0.4541977567 0.2443559649 0.3787195727
#> [46] 0.7902178841 0.2959092770 0.7714983481 0.7714983481 0.1209257020
#> [51] 0.6812372602 0.0929685502 0.5591566628 0.2237518926 0.6411640964
#> [56] 0.0295122566 0.4977685942 0.3787195727 0.4329019765 0.3369386352
#> [61] 0.4866238141 0.4109923177 0.0667402389 0.8990587768 0.5591566628
#> [66] 0.1209257020 0.2443559649 0.4001434491 0.9590962077 0.8092280927
#> [71] 0.0839693227 0.3575058758 0.9590962077 0.4541977567 0.4434976291
#> [76] 0.0435134601 0.6514201648 0.3680703543 0.8282107467 0.0187155630
#> [81] 0.0929685502 0.9341232519 0.4977685942 0.1632341963 0.9341232519
#> [86] 0.0044823216 0.4977685942 0.8282107467 0.2649922073 0.8813983793
#> [91] 0.9590962077 0.6007997897 0.3162587528 0.7012921295 0.8282107467
#> [96] 0.5902880909 0.1209257020 0.1874894736 0.7113770806 0.0187155630
#> [101] 0.6209496971 0.8813983793 0.0753183403 0.9838607452 0.9508331866
#> [106] 0.5385497978 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000
#>
#> $Time
#> 183 123 14 177 145 171 164 66 85 90 155 78 78.1
#> 9.24 13.00 12.89 12.53 10.07 16.57 23.60 22.13 16.44 20.94 13.08 23.88 23.88
#> 14.1 51 130 158 187 164.1 30 26 25 107 49 57 167
#> 12.89 18.23 16.47 20.14 9.92 23.60 17.43 15.77 6.32 11.18 12.19 14.46 15.55
#> 56 78.2 197 175 79 24 139 169 133 107.1 170 105 190
#> 12.21 23.88 21.60 21.91 16.23 23.89 21.49 22.41 14.65 11.18 19.54 19.75 20.81
#> 168 140 153 110 99 8 177.1 68 154 154.1 66.1 96 169.1
#> 23.72 12.68 21.33 17.56 21.19 18.43 12.53 20.62 12.63 12.63 22.13 14.54 22.41
#> 181 153.1 6 168.1 106 8.1 40 170.1 23 51.1 69 93 181.1
#> 16.46 21.33 15.64 23.72 16.67 18.43 18.00 19.54 16.92 18.23 23.23 10.33 16.46
#> 66.2 36 108 77 37 113 58 77.1 110.1 184 164.2 167.1 97
#> 22.13 21.19 18.29 7.27 12.52 22.86 19.34 7.27 17.56 17.77 23.60 15.55 19.14
#> 49.1 86 169.2 149 106.1 175.1 149.1 78.3 106.2 49.2 90.1 52 77.2
#> 12.19 23.81 22.41 8.37 16.67 21.91 8.37 23.88 16.67 12.19 20.94 10.42 7.27
#> 79.1 166 81 49.3 5 66.3 136 155.1 86.1 26.1 52.1 92 25.1
#> 16.23 19.98 14.06 12.19 16.43 22.13 21.83 13.08 23.81 15.77 10.42 22.92 6.32
#> 70 130.1 62 53 47 34 87 83 176 118 120 119 109
#> 7.38 16.47 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 67 83.1 9.1 1 182 162 200 83.2 165 118.1 173 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 116 64 12 137 131 95 34.1 94 87.1 200.1 53.1 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 172 160 156 22 162.1 12.1 38 87.2 173.1 17 12.2 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 28.1 135 65 148 143 33 2 198 144.1 83.3 12.3 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 82 160.1 141 54 131.1 83.4 191 135.1 72 19 46 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.1 132 131.2 74 80 28.2 34.2 173.2 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[32]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.02070804 0.46919730 0.15585998
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.17911402 0.02066476 0.33749500
#> grade_iii, Cure model
#> 0.70094060
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 157 15.10 1 47 0 0
#> 101 9.97 1 10 0 1
#> 117 17.46 1 26 0 1
#> 167 15.55 1 56 1 0
#> 106 16.67 1 49 1 0
#> 45 17.42 1 54 0 1
#> 169 22.41 1 46 0 0
#> 97 19.14 1 65 0 1
#> 10 10.53 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 100 16.07 1 60 0 0
#> 183 9.24 1 67 1 0
#> 106.1 16.67 1 49 1 0
#> 59 10.16 1 NA 1 0
#> 183.1 9.24 1 67 1 0
#> 113 22.86 1 34 0 0
#> 140 12.68 1 59 1 0
#> 106.2 16.67 1 49 1 0
#> 29 15.45 1 68 1 0
#> 134 17.81 1 47 1 0
#> 194 22.40 1 38 0 1
#> 199 19.81 1 NA 0 1
#> 90 20.94 1 50 0 1
#> 50 10.02 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 32 20.90 1 37 1 0
#> 157.1 15.10 1 47 0 0
#> 24 23.89 1 38 0 0
#> 169.1 22.41 1 46 0 0
#> 77 7.27 1 67 0 1
#> 37 12.52 1 57 1 0
#> 123 13.00 1 44 1 0
#> 96 14.54 1 33 0 1
#> 86 23.81 1 58 0 1
#> 16 8.71 1 71 0 1
#> 106.3 16.67 1 49 1 0
#> 36 21.19 1 48 0 1
#> 114 13.68 1 NA 0 0
#> 76 19.22 1 54 0 1
#> 133 14.65 1 57 0 0
#> 153 21.33 1 55 1 0
#> 41 18.02 1 40 1 0
#> 190 20.81 1 42 1 0
#> 63 22.77 1 31 1 0
#> 194.1 22.40 1 38 0 1
#> 97.1 19.14 1 65 0 1
#> 145 10.07 1 65 1 0
#> 41.1 18.02 1 40 1 0
#> 124 9.73 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 171 16.57 1 41 0 1
#> 88 18.37 1 47 0 0
#> 100.1 16.07 1 60 0 0
#> 157.2 15.10 1 47 0 0
#> 158 20.14 1 74 1 0
#> 69 23.23 1 25 0 1
#> 114.1 13.68 1 NA 0 0
#> 110 17.56 1 65 0 1
#> 157.3 15.10 1 47 0 0
#> 63.1 22.77 1 31 1 0
#> 51 18.23 1 83 0 1
#> 32.1 20.90 1 37 1 0
#> 86.1 23.81 1 58 0 1
#> 93 10.33 1 52 0 1
#> 183.2 9.24 1 67 1 0
#> 130 16.47 1 53 0 1
#> 8 18.43 1 32 0 0
#> 145.1 10.07 1 65 1 0
#> 130.1 16.47 1 53 0 1
#> 10.1 10.53 1 34 0 0
#> 93.1 10.33 1 52 0 1
#> 101.1 9.97 1 10 0 1
#> 124.1 9.73 1 NA 1 0
#> 32.2 20.90 1 37 1 0
#> 188 16.16 1 46 0 1
#> 117.1 17.46 1 26 0 1
#> 15 22.68 1 48 0 0
#> 177 12.53 1 75 0 0
#> 175 21.91 1 43 0 0
#> 199.1 19.81 1 NA 0 1
#> 140.1 12.68 1 59 1 0
#> 18 15.21 1 49 1 0
#> 128 20.35 1 35 0 1
#> 125 15.65 1 67 1 0
#> 69.1 23.23 1 25 0 1
#> 145.2 10.07 1 65 1 0
#> 197 21.60 1 69 1 0
#> 130.2 16.47 1 53 0 1
#> 192 16.44 1 31 1 0
#> 81 14.06 1 34 0 0
#> 37.1 12.52 1 57 1 0
#> 92 22.92 1 47 0 1
#> 181 16.46 1 45 0 1
#> 153.1 21.33 1 55 1 0
#> 59.1 10.16 1 NA 1 0
#> 113.1 22.86 1 34 0 0
#> 197.1 21.60 1 69 1 0
#> 23 16.92 1 61 0 0
#> 124.2 9.73 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 145.3 10.07 1 65 1 0
#> 63.2 22.77 1 31 1 0
#> 188.1 16.16 1 46 0 1
#> 30 17.43 1 78 0 0
#> 91 5.33 1 61 0 1
#> 171.1 16.57 1 41 0 1
#> 145.4 10.07 1 65 1 0
#> 52 10.42 1 52 0 1
#> 66 22.13 1 53 0 0
#> 166 19.98 1 48 0 0
#> 114.2 13.68 1 NA 0 0
#> 88.1 18.37 1 47 0 0
#> 116 24.00 0 58 0 1
#> 174 24.00 0 49 1 0
#> 148 24.00 0 61 1 0
#> 146 24.00 0 63 1 0
#> 21 24.00 0 47 0 0
#> 19 24.00 0 57 0 1
#> 87 24.00 0 27 0 0
#> 132 24.00 0 55 0 0
#> 28 24.00 0 67 1 0
#> 198 24.00 0 66 0 1
#> 161 24.00 0 45 0 0
#> 182 24.00 0 35 0 0
#> 33 24.00 0 53 0 0
#> 115 24.00 0 NA 1 0
#> 17 24.00 0 38 0 1
#> 120 24.00 0 68 0 1
#> 74 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 143 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 44 24.00 0 56 0 0
#> 109 24.00 0 48 0 0
#> 38 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 17.1 24.00 0 38 0 1
#> 84 24.00 0 39 0 1
#> 19.1 24.00 0 57 0 1
#> 9 24.00 0 31 1 0
#> 19.2 24.00 0 57 0 1
#> 2 24.00 0 9 0 0
#> 87.1 24.00 0 27 0 0
#> 22 24.00 0 52 1 0
#> 118 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 1 24.00 0 23 1 0
#> 198.1 24.00 0 66 0 1
#> 176 24.00 0 43 0 1
#> 83 24.00 0 6 0 0
#> 131.1 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 19.3 24.00 0 57 0 1
#> 160 24.00 0 31 1 0
#> 176.1 24.00 0 43 0 1
#> 152 24.00 0 36 0 1
#> 163 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 84.1 24.00 0 39 0 1
#> 75 24.00 0 21 1 0
#> 172 24.00 0 41 0 0
#> 22.1 24.00 0 52 1 0
#> 7 24.00 0 37 1 0
#> 135 24.00 0 58 1 0
#> 142.1 24.00 0 53 0 0
#> 54 24.00 0 53 1 0
#> 178 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 143.1 24.00 0 51 0 0
#> 33.1 24.00 0 53 0 0
#> 156 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 35 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 185 24.00 0 44 1 0
#> 75.1 24.00 0 21 1 0
#> 161.1 24.00 0 45 0 0
#> 196 24.00 0 19 0 0
#> 48 24.00 0 31 1 0
#> 161.2 24.00 0 45 0 0
#> 131.2 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 178.1 24.00 0 52 1 0
#> 67 24.00 0 25 0 0
#> 72 24.00 0 40 0 1
#> 20.1 24.00 0 46 1 0
#> 3.1 24.00 0 31 1 0
#> 48.1 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 38.1 24.00 0 31 1 0
#> 143.2 24.00 0 51 0 0
#> 3.2 24.00 0 31 1 0
#> 7.1 24.00 0 37 1 0
#> 34 24.00 0 36 0 0
#> 191 24.00 0 60 0 1
#> 3.3 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.18 NA NA NA
#> 2 age, Cure model 0.0207 NA NA NA
#> 3 grade_ii, Cure model 0.337 NA NA NA
#> 4 grade_iii, Cure model 0.701 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0207 NA NA NA
#> 2 grade_ii, Survival model 0.469 NA NA NA
#> 3 grade_iii, Survival model 0.156 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.17911 0.02066 0.33750 0.70094
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 251.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.17911402 0.02066476 0.33749500 0.70094060
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.02070804 0.46919730 0.15585998
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9000924 0.9752406 0.7960872 0.8888351 0.8211360 0.8113451 0.5432014
#> [8] 0.7390560 0.9450113 0.8769693 0.9810004 0.8211360 0.9810004 0.4422103
#> [15] 0.9284853 0.8211360 0.8926643 0.7855499 0.5707268 0.6744447 0.6578101
#> [22] 0.6825825 0.9000924 0.1616422 0.5432014 0.9946642 0.9385544 0.9249977
#> [29] 0.9179295 0.3162359 0.9892363 0.8211360 0.6578101 0.7325789 0.9143704
#> [36] 0.6403535 0.7746889 0.7047914 0.4815619 0.5707268 0.7390560 0.9608677
#> [43] 0.7746889 0.2548401 0.8389704 0.7572702 0.8769693 0.9000924 0.7192182
#> [50] 0.3715792 0.7908798 0.9000924 0.4815619 0.7690274 0.6825825 0.3162359
#> [57] 0.9546089 0.9810004 0.8477727 0.7512131 0.9608677 0.8477727 0.9450113
#> [64] 0.9546089 0.9752406 0.6825825 0.8688189 0.7960872 0.5280190 0.9352238
#> [71] 0.6087178 0.9284853 0.8964046 0.7120564 0.8849372 0.3715792 0.9608677
#> [78] 0.6207645 0.8477727 0.8646546 0.9214705 0.9385544 0.4200121 0.8604491
#> [85] 0.6403535 0.4422103 0.6207645 0.8162778 0.9919583 0.9608677 0.4815619
#> [92] 0.8688189 0.8063340 0.9973433 0.8389704 0.9608677 0.9514235 0.5963186
#> [99] 0.7259509 0.7572702 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 157 101 117 167 106 45 169 97 10 100 183 106.1 183.1
#> 15.10 9.97 17.46 15.55 16.67 17.42 22.41 19.14 10.53 16.07 9.24 16.67 9.24
#> 113 140 106.2 29 134 194 90 99 32 157.1 24 169.1 77
#> 22.86 12.68 16.67 15.45 17.81 22.40 20.94 21.19 20.90 15.10 23.89 22.41 7.27
#> 37 123 96 86 16 106.3 36 76 133 153 41 190 63
#> 12.52 13.00 14.54 23.81 8.71 16.67 21.19 19.22 14.65 21.33 18.02 20.81 22.77
#> 194.1 97.1 145 41.1 78 171 88 100.1 157.2 158 69 110 157.3
#> 22.40 19.14 10.07 18.02 23.88 16.57 18.37 16.07 15.10 20.14 23.23 17.56 15.10
#> 63.1 51 32.1 86.1 93 183.2 130 8 145.1 130.1 10.1 93.1 101.1
#> 22.77 18.23 20.90 23.81 10.33 9.24 16.47 18.43 10.07 16.47 10.53 10.33 9.97
#> 32.2 188 117.1 15 177 175 140.1 18 128 125 69.1 145.2 197
#> 20.90 16.16 17.46 22.68 12.53 21.91 12.68 15.21 20.35 15.65 23.23 10.07 21.60
#> 130.2 192 81 37.1 92 181 153.1 113.1 197.1 23 149 145.3 63.2
#> 16.47 16.44 14.06 12.52 22.92 16.46 21.33 22.86 21.60 16.92 8.37 10.07 22.77
#> 188.1 30 91 171.1 145.4 52 66 166 88.1 116 174 148 146
#> 16.16 17.43 5.33 16.57 10.07 10.42 22.13 19.98 18.37 24.00 24.00 24.00 24.00
#> 21 19 87 132 28 198 161 182 33 17 120 74 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 142 44 109 38 104 3 131 12 17.1 84 19.1 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.2 2 87.1 22 118 80 1 198.1 176 83 131.1 94 19.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 176.1 152 163 62 84.1 75 172 22.1 7 135 142.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 20 143.1 33.1 156 11 35 47 185 75.1 161.1 196 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.2 131.2 141 162 178.1 67 72 20.1 3.1 48.1 53 38.1 143.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.2 7.1 34 191 3.3
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[33]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001115682 0.531686555 0.635554809
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.405658265 0.009837939 -0.204996760
#> grade_iii, Cure model
#> 0.372404985
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 99 21.19 1 38 0 1
#> 153 21.33 1 55 1 0
#> 15 22.68 1 48 0 0
#> 158 20.14 1 74 1 0
#> 43 12.10 1 61 0 1
#> 50 10.02 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 57 14.46 1 45 0 1
#> 184 17.77 1 38 0 0
#> 89 11.44 1 NA 0 0
#> 93 10.33 1 52 0 1
#> 26 15.77 1 49 0 1
#> 23 16.92 1 61 0 0
#> 127 3.53 1 62 0 1
#> 42 12.43 1 49 0 1
#> 169 22.41 1 46 0 0
#> 190 20.81 1 42 1 0
#> 56 12.21 1 60 0 0
#> 88 18.37 1 47 0 0
#> 149 8.37 1 33 1 0
#> 4 17.64 1 NA 0 1
#> 170 19.54 1 43 0 1
#> 68 20.62 1 44 0 0
#> 123 13.00 1 44 1 0
#> 88.1 18.37 1 47 0 0
#> 183 9.24 1 67 1 0
#> 100 16.07 1 60 0 0
#> 124 9.73 1 NA 1 0
#> 56.1 12.21 1 60 0 0
#> 154 12.63 1 20 1 0
#> 123.1 13.00 1 44 1 0
#> 139 21.49 1 63 1 0
#> 56.2 12.21 1 60 0 0
#> 14 12.89 1 21 0 0
#> 188 16.16 1 46 0 1
#> 179 18.63 1 42 0 0
#> 59 10.16 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 24 23.89 1 38 0 0
#> 52 10.42 1 52 0 1
#> 81 14.06 1 34 0 0
#> 40 18.00 1 28 1 0
#> 93.1 10.33 1 52 0 1
#> 199 19.81 1 NA 0 1
#> 86 23.81 1 58 0 1
#> 187 9.92 1 39 1 0
#> 101 9.97 1 10 0 1
#> 61 10.12 1 36 0 1
#> 170.1 19.54 1 43 0 1
#> 41 18.02 1 40 1 0
#> 124.1 9.73 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 110.1 17.56 1 65 0 1
#> 175 21.91 1 43 0 0
#> 78 23.88 1 43 0 0
#> 57.1 14.46 1 45 0 1
#> 105 19.75 1 60 0 0
#> 188.1 16.16 1 46 0 1
#> 199.1 19.81 1 NA 0 1
#> 56.3 12.21 1 60 0 0
#> 124.2 9.73 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 45 17.42 1 54 0 1
#> 91 5.33 1 61 0 1
#> 61.1 10.12 1 36 0 1
#> 8 18.43 1 32 0 0
#> 96 14.54 1 33 0 1
#> 52.1 10.42 1 52 0 1
#> 124.3 9.73 1 NA 1 0
#> 159.1 10.55 1 50 0 1
#> 139.1 21.49 1 63 1 0
#> 42.1 12.43 1 49 0 1
#> 184.1 17.77 1 38 0 0
#> 158.1 20.14 1 74 1 0
#> 42.2 12.43 1 49 0 1
#> 70 7.38 1 30 1 0
#> 192 16.44 1 31 1 0
#> 145 10.07 1 65 1 0
#> 92 22.92 1 47 0 1
#> 63 22.77 1 31 1 0
#> 81.1 14.06 1 34 0 0
#> 136 21.83 1 43 0 1
#> 40.1 18.00 1 28 1 0
#> 169.2 22.41 1 46 0 0
#> 6.1 15.64 1 39 0 0
#> 111 17.45 1 47 0 1
#> 194 22.40 1 38 0 1
#> 179.1 18.63 1 42 0 0
#> 133 14.65 1 57 0 0
#> 188.2 16.16 1 46 0 1
#> 175.1 21.91 1 43 0 0
#> 179.2 18.63 1 42 0 0
#> 192.1 16.44 1 31 1 0
#> 90 20.94 1 50 0 1
#> 179.3 18.63 1 42 0 0
#> 25 6.32 1 34 1 0
#> 195 11.76 1 NA 1 0
#> 4.1 17.64 1 NA 0 1
#> 100.1 16.07 1 60 0 0
#> 134 17.81 1 47 1 0
#> 99.1 21.19 1 38 0 1
#> 36 21.19 1 48 0 1
#> 171 16.57 1 41 0 1
#> 76 19.22 1 54 0 1
#> 58 19.34 1 39 0 0
#> 127.1 3.53 1 62 0 1
#> 78.1 23.88 1 43 0 0
#> 58.1 19.34 1 39 0 0
#> 110.2 17.56 1 65 0 1
#> 168 23.72 1 70 0 0
#> 16 8.71 1 71 0 1
#> 50.1 10.02 1 NA 1 0
#> 112 24.00 0 61 0 0
#> 3 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 147 24.00 0 76 1 0
#> 126 24.00 0 48 0 0
#> 21 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 33 24.00 0 53 0 0
#> 102 24.00 0 49 0 0
#> 54 24.00 0 53 1 0
#> 152 24.00 0 36 0 1
#> 53 24.00 0 32 0 1
#> 12 24.00 0 63 0 0
#> 9.1 24.00 0 31 1 0
#> 147.1 24.00 0 76 1 0
#> 161 24.00 0 45 0 0
#> 186 24.00 0 45 1 0
#> 84 24.00 0 39 0 1
#> 34 24.00 0 36 0 0
#> 103 24.00 0 56 1 0
#> 152.1 24.00 0 36 0 1
#> 83 24.00 0 6 0 0
#> 38 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 186.1 24.00 0 45 1 0
#> 173 24.00 0 19 0 1
#> 80 24.00 0 41 0 0
#> 84.1 24.00 0 39 0 1
#> 19 24.00 0 57 0 1
#> 132 24.00 0 55 0 0
#> 160 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 135 24.00 0 58 1 0
#> 176 24.00 0 43 0 1
#> 173.1 24.00 0 19 0 1
#> 87 24.00 0 27 0 0
#> 53.1 24.00 0 32 0 1
#> 27 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 22 24.00 0 52 1 0
#> 191 24.00 0 60 0 1
#> 47 24.00 0 38 0 1
#> 126.1 24.00 0 48 0 0
#> 161.1 24.00 0 45 0 0
#> 62 24.00 0 71 0 0
#> 193 24.00 0 45 0 1
#> 75 24.00 0 21 1 0
#> 163 24.00 0 66 0 0
#> 152.2 24.00 0 36 0 1
#> 53.2 24.00 0 32 0 1
#> 131 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 120.1 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 135.1 24.00 0 58 1 0
#> 132.1 24.00 0 55 0 0
#> 160.1 24.00 0 31 1 0
#> 186.2 24.00 0 45 1 0
#> 161.2 24.00 0 45 0 0
#> 173.2 24.00 0 19 0 1
#> 102.1 24.00 0 49 0 0
#> 65 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 198 24.00 0 66 0 1
#> 1 24.00 0 23 1 0
#> 152.3 24.00 0 36 0 1
#> 17.1 24.00 0 38 0 1
#> 148 24.00 0 61 1 0
#> 82 24.00 0 34 0 0
#> 38.1 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 102.2 24.00 0 49 0 0
#> 109 24.00 0 48 0 0
#> 12.1 24.00 0 63 0 0
#> 132.2 24.00 0 55 0 0
#> 115 24.00 0 NA 1 0
#> 82.1 24.00 0 34 0 0
#> 162 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 33.1 24.00 0 53 0 0
#> 142 24.00 0 53 0 0
#> 1.1 24.00 0 23 1 0
#> 11 24.00 0 42 0 1
#> 191.1 24.00 0 60 0 1
#> 80.1 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.406 NA NA NA
#> 2 age, Cure model 0.00984 NA NA NA
#> 3 grade_ii, Cure model -0.205 NA NA NA
#> 4 grade_iii, Cure model 0.372 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00112 NA NA NA
#> 2 grade_ii, Survival model 0.532 NA NA NA
#> 3 grade_iii, Survival model 0.636 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.405658 0.009838 -0.204997 0.372405
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 257.1
#> Residual Deviance: 253.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.405658265 0.009837939 -0.204996760 0.372404985
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001115682 0.531686555 0.635554809
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.29786452 0.28523518 0.14560215 0.36385429 0.85378212 0.86156550
#> [7] 0.73500523 0.55213510 0.89192124 0.69325384 0.61624198 0.98612409
#> [13] 0.79961355 0.16100776 0.34205316 0.82285937 0.49384062 0.95775440
#> [19] 0.39520921 0.35294565 0.76749723 0.49384062 0.94335694 0.67644147
#> [25] 0.82285937 0.79160342 0.76749723 0.25987702 0.82285937 0.78353909
#> [31] 0.65142030 0.44519891 0.57105790 0.01341793 0.87684604 0.75124468
#> [37] 0.52350757 0.89192124 0.07655629 0.93610578 0.92881909 0.90679989
#> [43] 0.39520921 0.51363413 0.70163113 0.57105790 0.21798828 0.03808799
#> [49] 0.73500523 0.38464876 0.65142030 0.82285937 0.16100776 0.60727056
#> [55] 0.97908584 0.90679989 0.48386335 0.72669323 0.87684604 0.86156550
#> [61] 0.25987702 0.79961355 0.55213510 0.36385429 0.79961355 0.96489856
#> [67] 0.63409955 0.92148250 0.11371215 0.13028249 0.75124468 0.24606331
#> [73] 0.52350757 0.16100776 0.70163113 0.59819488 0.20355979 0.44519891
#> [79] 0.71830255 0.65142030 0.21798828 0.44519891 0.63409955 0.33093993
#> [85] 0.44519891 0.97200873 0.67644147 0.54260493 0.29786452 0.29786452
#> [91] 0.62522200 0.43524253 0.41520524 0.98612409 0.03808799 0.41520524
#> [97] 0.57105790 0.09499233 0.95057595 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 99 153 15 158 43 159 57 184 93 26 23 127 42
#> 21.19 21.33 22.68 20.14 12.10 10.55 14.46 17.77 10.33 15.77 16.92 3.53 12.43
#> 169 190 56 88 149 170 68 123 88.1 183 100 56.1 154
#> 22.41 20.81 12.21 18.37 8.37 19.54 20.62 13.00 18.37 9.24 16.07 12.21 12.63
#> 123.1 139 56.2 14 188 179 110 24 52 81 40 93.1 86
#> 13.00 21.49 12.21 12.89 16.16 18.63 17.56 23.89 10.42 14.06 18.00 10.33 23.81
#> 187 101 61 170.1 41 6 110.1 175 78 57.1 105 188.1 56.3
#> 9.92 9.97 10.12 19.54 18.02 15.64 17.56 21.91 23.88 14.46 19.75 16.16 12.21
#> 169.1 45 91 61.1 8 96 52.1 159.1 139.1 42.1 184.1 158.1 42.2
#> 22.41 17.42 5.33 10.12 18.43 14.54 10.42 10.55 21.49 12.43 17.77 20.14 12.43
#> 70 192 145 92 63 81.1 136 40.1 169.2 6.1 111 194 179.1
#> 7.38 16.44 10.07 22.92 22.77 14.06 21.83 18.00 22.41 15.64 17.45 22.40 18.63
#> 133 188.2 175.1 179.2 192.1 90 179.3 25 100.1 134 99.1 36 171
#> 14.65 16.16 21.91 18.63 16.44 20.94 18.63 6.32 16.07 17.81 21.19 21.19 16.57
#> 76 58 127.1 78.1 58.1 110.2 168 16 112 3 120 147 126
#> 19.22 19.34 3.53 23.88 19.34 17.56 23.72 8.71 24.00 24.00 24.00 24.00 24.00
#> 21 9 104 143 33 102 54 152 53 12 9.1 147.1 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 84 34 103 152.1 83 38 165 186.1 173 80 84.1 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 160 74 172 135 176 173.1 87 53.1 27 17 22 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 126.1 161.1 62 193 75 163 152.2 53.2 131 178 120.1 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 132.1 160.1 186.2 161.2 173.2 102.1 65 20 198 1 152.3 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 82 38.1 182 102.2 109 12.1 132.2 82.1 162 116 33.1 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 11 191.1 80.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[34]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.007260547 0.433427578 0.399961414
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.3614124 0.0108501 -0.3271305
#> grade_iii, Cure model
#> 0.4971257
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 107 11.18 1 54 1 0
#> 90 20.94 1 50 0 1
#> 180 14.82 1 37 0 0
#> 105 19.75 1 60 0 0
#> 111 17.45 1 47 0 1
#> 136 21.83 1 43 0 1
#> 41 18.02 1 40 1 0
#> 51 18.23 1 83 0 1
#> 134 17.81 1 47 1 0
#> 76 19.22 1 54 0 1
#> 45 17.42 1 54 0 1
#> 188 16.16 1 46 0 1
#> 157 15.10 1 47 0 0
#> 97 19.14 1 65 0 1
#> 50 10.02 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 93 10.33 1 52 0 1
#> 37 12.52 1 57 1 0
#> 96 14.54 1 33 0 1
#> 171 16.57 1 41 0 1
#> 99 21.19 1 38 0 1
#> 166 19.98 1 48 0 0
#> 41.1 18.02 1 40 1 0
#> 199 19.81 1 NA 0 1
#> 183 9.24 1 67 1 0
#> 55 19.34 1 69 0 1
#> 197 21.60 1 69 1 0
#> 85 16.44 1 36 0 0
#> 37.1 12.52 1 57 1 0
#> 150 20.33 1 48 0 0
#> 91 5.33 1 61 0 1
#> 91.1 5.33 1 61 0 1
#> 179 18.63 1 42 0 0
#> 101 9.97 1 10 0 1
#> 86 23.81 1 58 0 1
#> 177 12.53 1 75 0 0
#> 129 23.41 1 53 1 0
#> 139 21.49 1 63 1 0
#> 29 15.45 1 68 1 0
#> 136.1 21.83 1 43 0 1
#> 180.1 14.82 1 37 0 0
#> 114 13.68 1 NA 0 0
#> 76.1 19.22 1 54 0 1
#> 30 17.43 1 78 0 0
#> 60 13.15 1 38 1 0
#> 134.1 17.81 1 47 1 0
#> 77 7.27 1 67 0 1
#> 41.2 18.02 1 40 1 0
#> 195 11.76 1 NA 1 0
#> 81 14.06 1 34 0 0
#> 195.1 11.76 1 NA 1 0
#> 16 8.71 1 71 0 1
#> 81.1 14.06 1 34 0 0
#> 68 20.62 1 44 0 0
#> 181 16.46 1 45 0 1
#> 79 16.23 1 54 1 0
#> 42 12.43 1 49 0 1
#> 183.1 9.24 1 67 1 0
#> 26 15.77 1 49 0 1
#> 25 6.32 1 34 1 0
#> 69 23.23 1 25 0 1
#> 66 22.13 1 53 0 0
#> 145 10.07 1 65 1 0
#> 24 23.89 1 38 0 0
#> 114.1 13.68 1 NA 0 0
#> 134.2 17.81 1 47 1 0
#> 58 19.34 1 39 0 0
#> 10 10.53 1 34 0 0
#> 26.1 15.77 1 49 0 1
#> 63 22.77 1 31 1 0
#> 155 13.08 1 26 0 0
#> 30.1 17.43 1 78 0 0
#> 150.1 20.33 1 48 0 0
#> 168 23.72 1 70 0 0
#> 8 18.43 1 32 0 0
#> 105.1 19.75 1 60 0 0
#> 76.2 19.22 1 54 0 1
#> 90.1 20.94 1 50 0 1
#> 127 3.53 1 62 0 1
#> 96.1 14.54 1 33 0 1
#> 175 21.91 1 43 0 0
#> 15 22.68 1 48 0 0
#> 14 12.89 1 21 0 0
#> 106 16.67 1 49 1 0
#> 188.1 16.16 1 46 0 1
#> 180.2 14.82 1 37 0 0
#> 93.1 10.33 1 52 0 1
#> 190 20.81 1 42 1 0
#> 63.1 22.77 1 31 1 0
#> 166.1 19.98 1 48 0 0
#> 61 10.12 1 36 0 1
#> 37.2 12.52 1 57 1 0
#> 88 18.37 1 47 0 0
#> 170 19.54 1 43 0 1
#> 150.2 20.33 1 48 0 0
#> 183.2 9.24 1 67 1 0
#> 169 22.41 1 46 0 0
#> 101.1 9.97 1 10 0 1
#> 123 13.00 1 44 1 0
#> 58.1 19.34 1 39 0 0
#> 134.3 17.81 1 47 1 0
#> 184 17.77 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 110 17.56 1 65 0 1
#> 57 14.46 1 45 0 1
#> 110.1 17.56 1 65 0 1
#> 85.1 16.44 1 36 0 0
#> 91.2 5.33 1 61 0 1
#> 167 15.55 1 56 1 0
#> 89 11.44 1 NA 0 0
#> 55.1 19.34 1 69 0 1
#> 128 20.35 1 35 0 1
#> 115 24.00 0 NA 1 0
#> 161 24.00 0 45 0 0
#> 98 24.00 0 34 1 0
#> 144 24.00 0 28 0 1
#> 71 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 162 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 196 24.00 0 19 0 0
#> 135 24.00 0 58 1 0
#> 102 24.00 0 49 0 0
#> 116 24.00 0 58 0 1
#> 146 24.00 0 63 1 0
#> 118 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 31 24.00 0 36 0 1
#> 162.1 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 103 24.00 0 56 1 0
#> 3 24.00 0 31 1 0
#> 116.1 24.00 0 58 0 1
#> 84 24.00 0 39 0 1
#> 3.1 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 65 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 151 24.00 0 42 0 0
#> 3.2 24.00 0 31 1 0
#> 72.1 24.00 0 40 0 1
#> 62 24.00 0 71 0 0
#> 94 24.00 0 51 0 1
#> 53 24.00 0 32 0 1
#> 176 24.00 0 43 0 1
#> 20 24.00 0 46 1 0
#> 65.1 24.00 0 57 1 0
#> 132 24.00 0 55 0 0
#> 126 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 22 24.00 0 52 1 0
#> 3.3 24.00 0 31 1 0
#> 20.1 24.00 0 46 1 0
#> 173 24.00 0 19 0 1
#> 65.2 24.00 0 57 1 0
#> 33 24.00 0 53 0 0
#> 73 24.00 0 NA 0 1
#> 94.1 24.00 0 51 0 1
#> 174 24.00 0 49 1 0
#> 142 24.00 0 53 0 0
#> 64.1 24.00 0 43 0 0
#> 80 24.00 0 41 0 0
#> 160 24.00 0 31 1 0
#> 176.1 24.00 0 43 0 1
#> 120 24.00 0 68 0 1
#> 121 24.00 0 57 1 0
#> 1 24.00 0 23 1 0
#> 163 24.00 0 66 0 0
#> 115.1 24.00 0 NA 1 0
#> 163.1 24.00 0 66 0 0
#> 174.1 24.00 0 49 1 0
#> 62.1 24.00 0 71 0 0
#> 116.2 24.00 0 58 0 1
#> 71.1 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 174.2 24.00 0 49 1 0
#> 21 24.00 0 47 0 0
#> 47 24.00 0 38 0 1
#> 148 24.00 0 61 1 0
#> 62.2 24.00 0 71 0 0
#> 9.1 24.00 0 31 1 0
#> 162.2 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 48 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 121.1 24.00 0 57 1 0
#> 21.1 24.00 0 47 0 0
#> 147 24.00 0 76 1 0
#> 144.1 24.00 0 28 0 1
#> 84.1 24.00 0 39 0 1
#> 3.4 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 151.1 24.00 0 42 0 0
#> 47.1 24.00 0 38 0 1
#> 54.1 24.00 0 53 1 0
#> 54.2 24.00 0 53 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.361 NA NA NA
#> 2 age, Cure model 0.0109 NA NA NA
#> 3 grade_ii, Cure model -0.327 NA NA NA
#> 4 grade_iii, Cure model 0.497 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00726 NA NA NA
#> 2 grade_ii, Survival model 0.433 NA NA NA
#> 3 grade_iii, Survival model 0.400 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.36141 0.01085 -0.32713 0.49713
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.3
#> Residual Deviance: 255.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.3614124 0.0108501 -0.3271305 0.4971257
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.007260547 0.433427578 0.399961414
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.90629625 0.39497468 0.80787652 0.49731393 0.69824515 0.33207124
#> [7] 0.62608163 0.61814363 0.64869301 0.56061312 0.71872846 0.76466464
#> [13] 0.80182514 0.58544110 0.28714665 0.91730502 0.88407403 0.82577205
#> [19] 0.73213005 0.38323087 0.47777432 0.62608163 0.94945390 0.52591447
#> [25] 0.35843216 0.74527354 0.88407403 0.44826902 0.98022172 0.98022172
#> [31] 0.59367267 0.93886102 0.12623101 0.87833697 0.18019457 0.37112898
#> [37] 0.79575512 0.33207124 0.80787652 0.56061312 0.70516279 0.85516577
#> [43] 0.64869301 0.97004796 0.62608163 0.84347906 0.96490962 0.84347906
#> [49] 0.42733943 0.73873302 0.75822956 0.90074390 0.94945390 0.77725212
#> [55] 0.97514777 0.20178340 0.30244218 0.93351300 0.05909968 0.64869301
#> [61] 0.52591447 0.91180528 0.77725212 0.22169542 0.86098800 0.70516279
#> [67] 0.44826902 0.15475561 0.60186375 0.49731393 0.56061312 0.39497468
#> [73] 0.99506163 0.82577205 0.31738331 0.25450830 0.87257266 0.72546644
#> [79] 0.76466464 0.80787652 0.91730502 0.41665970 0.22169542 0.47777432
#> [85] 0.92811947 0.88407403 0.61002577 0.51644336 0.44826902 0.94945390
#> [91] 0.27102206 0.93886102 0.86680206 0.52591447 0.64869301 0.67712846
#> [97] 0.05909968 0.68432770 0.83759241 0.68432770 0.74527354 0.98022172
#> [103] 0.78961355 0.52591447 0.43791966 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 107 90 180 105 111 136 41 51 134 76 45 188 157
#> 11.18 20.94 14.82 19.75 17.45 21.83 18.02 18.23 17.81 19.22 17.42 16.16 15.10
#> 97 194 93 37 96 171 99 166 41.1 183 55 197 85
#> 19.14 22.40 10.33 12.52 14.54 16.57 21.19 19.98 18.02 9.24 19.34 21.60 16.44
#> 37.1 150 91 91.1 179 101 86 177 129 139 29 136.1 180.1
#> 12.52 20.33 5.33 5.33 18.63 9.97 23.81 12.53 23.41 21.49 15.45 21.83 14.82
#> 76.1 30 60 134.1 77 41.2 81 16 81.1 68 181 79 42
#> 19.22 17.43 13.15 17.81 7.27 18.02 14.06 8.71 14.06 20.62 16.46 16.23 12.43
#> 183.1 26 25 69 66 145 24 134.2 58 10 26.1 63 155
#> 9.24 15.77 6.32 23.23 22.13 10.07 23.89 17.81 19.34 10.53 15.77 22.77 13.08
#> 30.1 150.1 168 8 105.1 76.2 90.1 127 96.1 175 15 14 106
#> 17.43 20.33 23.72 18.43 19.75 19.22 20.94 3.53 14.54 21.91 22.68 12.89 16.67
#> 188.1 180.2 93.1 190 63.1 166.1 61 37.2 88 170 150.2 183.2 169
#> 16.16 14.82 10.33 20.81 22.77 19.98 10.12 12.52 18.37 19.54 20.33 9.24 22.41
#> 101.1 123 58.1 134.3 184 24.1 110 57 110.1 85.1 91.2 167 55.1
#> 9.97 13.00 19.34 17.81 17.77 23.89 17.56 14.46 17.56 16.44 5.33 15.55 19.34
#> 128 161 98 144 71 38 11 162 12 196 135 102 116
#> 20.35 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 118 72 31 162.1 64 103 3 116.1 84 3.1 46 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 143 193 151 3.2 72.1 62 94 53 176 20 65.1 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 9 54 22 3.3 20.1 173 65.2 33 94.1 174 142 64.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 160 176.1 120 121 1 163 163.1 174.1 62.1 116.2 71.1 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.2 21 47 148 62.2 9.1 162.2 182 48 178 121.1 21.1 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 84.1 3.4 191 151.1 47.1 54.1 54.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[35]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01453896 0.64880593 0.29295487
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.47741362 0.00595238 0.30163323
#> grade_iii, Cure model
#> 1.03508433
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 91 5.33 1 61 0 1
#> 101 9.97 1 10 0 1
#> 23 16.92 1 61 0 0
#> 36 21.19 1 48 0 1
#> 39 15.59 1 37 0 1
#> 150 20.33 1 48 0 0
#> 150.1 20.33 1 48 0 0
#> 51 18.23 1 83 0 1
#> 168 23.72 1 70 0 0
#> 192 16.44 1 31 1 0
#> 42 12.43 1 49 0 1
#> 167 15.55 1 56 1 0
#> 179 18.63 1 42 0 0
#> 113 22.86 1 34 0 0
#> 76 19.22 1 54 0 1
#> 128 20.35 1 35 0 1
#> 101.1 9.97 1 10 0 1
#> 188 16.16 1 46 0 1
#> 159 10.55 1 50 0 1
#> 79 16.23 1 54 1 0
#> 49 12.19 1 48 1 0
#> 194 22.40 1 38 0 1
#> 184 17.77 1 38 0 0
#> 15 22.68 1 48 0 0
#> 133 14.65 1 57 0 0
#> 140 12.68 1 59 1 0
#> 85 16.44 1 36 0 0
#> 37 12.52 1 57 1 0
#> 164 23.60 1 76 0 1
#> 37.1 12.52 1 57 1 0
#> 90 20.94 1 50 0 1
#> 78 23.88 1 43 0 0
#> 40 18.00 1 28 1 0
#> 149 8.37 1 33 1 0
#> 197 21.60 1 69 1 0
#> 60 13.15 1 38 1 0
#> 194.1 22.40 1 38 0 1
#> 37.2 12.52 1 57 1 0
#> 167.1 15.55 1 56 1 0
#> 37.3 12.52 1 57 1 0
#> 43 12.10 1 61 0 1
#> 36.1 21.19 1 48 0 1
#> 14 12.89 1 21 0 0
#> 77 7.27 1 67 0 1
#> 70 7.38 1 30 1 0
#> 55 19.34 1 69 0 1
#> 166 19.98 1 48 0 0
#> 29 15.45 1 68 1 0
#> 40.1 18.00 1 28 1 0
#> 96 14.54 1 33 0 1
#> 180 14.82 1 37 0 0
#> 15.1 22.68 1 48 0 0
#> 153 21.33 1 55 1 0
#> 5 16.43 1 51 0 1
#> 181 16.46 1 45 0 1
#> 63 22.77 1 31 1 0
#> 194.2 22.40 1 38 0 1
#> 111 17.45 1 47 0 1
#> 86 23.81 1 58 0 1
#> 91.1 5.33 1 61 0 1
#> 157 15.10 1 47 0 0
#> 93 10.33 1 52 0 1
#> 158 20.14 1 74 1 0
#> 57 14.46 1 45 0 1
#> 153.1 21.33 1 55 1 0
#> 70.1 7.38 1 30 1 0
#> 25 6.32 1 34 1 0
#> 39.1 15.59 1 37 0 1
#> 79.1 16.23 1 54 1 0
#> 97 19.14 1 65 0 1
#> 26 15.77 1 49 0 1
#> 181.1 16.46 1 45 0 1
#> 101.2 9.97 1 10 0 1
#> 150.2 20.33 1 48 0 0
#> 85.1 16.44 1 36 0 0
#> 49.1 12.19 1 48 1 0
#> 89 11.44 1 NA 0 0
#> 97.1 19.14 1 65 0 1
#> 91.2 5.33 1 61 0 1
#> 76.1 19.22 1 54 0 1
#> 105 19.75 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 197.1 21.60 1 69 1 0
#> 91.3 5.33 1 61 0 1
#> 133.1 14.65 1 57 0 0
#> 110 17.56 1 65 0 1
#> 70.2 7.38 1 30 1 0
#> 13 14.34 1 54 0 1
#> 85.2 16.44 1 36 0 0
#> 88 18.37 1 47 0 0
#> 177 12.53 1 75 0 0
#> 10 10.53 1 34 0 0
#> 50 10.02 1 NA 1 0
#> 181.2 16.46 1 45 0 1
#> 177.1 12.53 1 75 0 0
#> 107 11.18 1 54 1 0
#> 123 13.00 1 44 1 0
#> 56 12.21 1 60 0 0
#> 187 9.92 1 39 1 0
#> 10.1 10.53 1 34 0 0
#> 101.3 9.97 1 10 0 1
#> 97.2 19.14 1 65 0 1
#> 149.1 8.37 1 33 1 0
#> 23.1 16.92 1 61 0 0
#> 76.2 19.22 1 54 0 1
#> 68 20.62 1 44 0 0
#> 180.1 14.82 1 37 0 0
#> 136 21.83 1 43 0 1
#> 157.1 15.10 1 47 0 0
#> 124 9.73 1 NA 1 0
#> 180.2 14.82 1 37 0 0
#> 15.2 22.68 1 48 0 0
#> 144 24.00 0 28 0 1
#> 161 24.00 0 45 0 0
#> 44 24.00 0 56 0 0
#> 131 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 160 24.00 0 31 1 0
#> 44.1 24.00 0 56 0 0
#> 75 24.00 0 21 1 0
#> 143 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 102 24.00 0 49 0 0
#> 1 24.00 0 23 1 0
#> 198 24.00 0 66 0 1
#> 142.1 24.00 0 53 0 0
#> 74 24.00 0 43 0 1
#> 87 24.00 0 27 0 0
#> 146 24.00 0 63 1 0
#> 2.1 24.00 0 9 0 0
#> 9 24.00 0 31 1 0
#> 143.1 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 193 24.00 0 45 0 1
#> 35 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 28 24.00 0 67 1 0
#> 121 24.00 0 57 1 0
#> 146.1 24.00 0 63 1 0
#> 147 24.00 0 76 1 0
#> 65 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 115 24.00 0 NA 1 0
#> 33 24.00 0 53 0 0
#> 22 24.00 0 52 1 0
#> 84 24.00 0 39 0 1
#> 193.1 24.00 0 45 0 1
#> 80 24.00 0 41 0 0
#> 33.1 24.00 0 53 0 0
#> 64 24.00 0 43 0 0
#> 38 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 121.1 24.00 0 57 1 0
#> 200 24.00 0 64 0 0
#> 75.1 24.00 0 21 1 0
#> 162 24.00 0 51 0 0
#> 38.1 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 146.2 24.00 0 63 1 0
#> 34 24.00 0 36 0 0
#> 165 24.00 0 47 0 0
#> 163 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 144.1 24.00 0 28 0 1
#> 138 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 141.1 24.00 0 44 1 0
#> 62.1 24.00 0 71 0 0
#> 162.1 24.00 0 51 0 0
#> 2.2 24.00 0 9 0 0
#> 144.2 24.00 0 28 0 1
#> 84.1 24.00 0 39 0 1
#> 137 24.00 0 45 1 0
#> 142.2 24.00 0 53 0 0
#> 131.1 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 141.2 24.00 0 44 1 0
#> 137.1 24.00 0 45 1 0
#> 193.2 24.00 0 45 0 1
#> 152 24.00 0 36 0 1
#> 98 24.00 0 34 1 0
#> 182 24.00 0 35 0 0
#> 46 24.00 0 71 0 0
#> 191.1 24.00 0 60 0 1
#> 33.2 24.00 0 53 0 0
#> 103 24.00 0 56 1 0
#> 156 24.00 0 50 1 0
#> 165.1 24.00 0 47 0 0
#> 22.1 24.00 0 52 1 0
#> 21 24.00 0 47 0 0
#> 198.1 24.00 0 66 0 1
#> 11.1 24.00 0 42 0 1
#> 11.2 24.00 0 42 0 1
#> 172 24.00 0 41 0 0
#> 119 24.00 0 17 0 0
#> 48 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 82 24.00 0 34 0 0
#> 161.1 24.00 0 45 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.477 NA NA NA
#> 2 age, Cure model 0.00595 NA NA NA
#> 3 grade_ii, Cure model 0.302 NA NA NA
#> 4 grade_iii, Cure model 1.04 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0145 NA NA NA
#> 2 grade_ii, Survival model 0.649 NA NA NA
#> 3 grade_iii, Survival model 0.293 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.477414 0.005952 0.301633 1.035084
#>
#> Degrees of Freedom: 194 Total (i.e. Null); 191 Residual
#> Null Deviance: 268.1
#> Residual Deviance: 259 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.47741362 0.00595238 0.30163323 1.03508433
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01453896 0.64880593 0.29295487
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9494211550 0.7992359454 0.2540812247 0.0629676486 0.3903970592
#> [6] 0.0913247268 0.0913247268 0.2012309717 0.0022407453 0.3010629774
#> [11] 0.6735032038 0.4111405568 0.1840802079 0.0074416357 0.1380441449
#> [16] 0.0853224425 0.7992359454 0.3697103732 0.7481849921 0.3495799910
#> [21] 0.6982848007 0.0255921493 0.2271676663 0.0144355289 0.4971804971
#> [26] 0.5900194685 0.3010629774 0.6258282724 0.0044173080 0.6258282724
#> [31] 0.0736815897 0.0001407047 0.2101305882 0.8619046135 0.0429636477
#> [36] 0.5548544483 0.0255921493 0.6258282724 0.4111405568 0.6258282724
#> [41] 0.7230164583 0.0629676486 0.5782567773 0.9241957150 0.8870772740
#> [46] 0.1306882194 0.1166189304 0.4320450084 0.2101305882 0.5199445356
#> [51] 0.4642674717 0.0144355289 0.0528306520 0.3394412237 0.2727202110
#> [56] 0.0110537393 0.0255921493 0.2449844054 0.0009116318 0.9494211550
#> [61] 0.4427020339 0.7863213870 0.1099011033 0.5314975300 0.0528306520
#> [66] 0.8870772740 0.9368226170 0.3903970592 0.3495799910 0.1602698184
#> [71] 0.3800054854 0.2727202110 0.7992359454 0.0913247268 0.3010629774
#> [76] 0.6982848007 0.1602698184 0.9494211550 0.1380441449 0.1235370107
#> [81] 0.0429636477 0.9494211550 0.4971804971 0.2359954882 0.8870772740
#> [86] 0.5431271847 0.3010629774 0.1925610546 0.6018265599 0.7608581116
#> [91] 0.2727202110 0.6018265599 0.7355870072 0.5665567121 0.6858288556
#> [96] 0.8491559741 0.7608581116 0.7992359454 0.1602698184 0.8619046135
#> [101] 0.2540812247 0.1380441449 0.0794011853 0.4642674717 0.0380708382
#> [106] 0.4427020339 0.4642674717 0.0144355289 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 91 101 23 36 39 150 150.1 51 168 192 42 167 179
#> 5.33 9.97 16.92 21.19 15.59 20.33 20.33 18.23 23.72 16.44 12.43 15.55 18.63
#> 113 76 128 101.1 188 159 79 49 194 184 15 133 140
#> 22.86 19.22 20.35 9.97 16.16 10.55 16.23 12.19 22.40 17.77 22.68 14.65 12.68
#> 85 37 164 37.1 90 78 40 149 197 60 194.1 37.2 167.1
#> 16.44 12.52 23.60 12.52 20.94 23.88 18.00 8.37 21.60 13.15 22.40 12.52 15.55
#> 37.3 43 36.1 14 77 70 55 166 29 40.1 96 180 15.1
#> 12.52 12.10 21.19 12.89 7.27 7.38 19.34 19.98 15.45 18.00 14.54 14.82 22.68
#> 153 5 181 63 194.2 111 86 91.1 157 93 158 57 153.1
#> 21.33 16.43 16.46 22.77 22.40 17.45 23.81 5.33 15.10 10.33 20.14 14.46 21.33
#> 70.1 25 39.1 79.1 97 26 181.1 101.2 150.2 85.1 49.1 97.1 91.2
#> 7.38 6.32 15.59 16.23 19.14 15.77 16.46 9.97 20.33 16.44 12.19 19.14 5.33
#> 76.1 105 197.1 91.3 133.1 110 70.2 13 85.2 88 177 10 181.2
#> 19.22 19.75 21.60 5.33 14.65 17.56 7.38 14.34 16.44 18.37 12.53 10.53 16.46
#> 177.1 107 123 56 187 10.1 101.3 97.2 149.1 23.1 76.2 68 180.1
#> 12.53 11.18 13.00 12.21 9.92 10.53 9.97 19.14 8.37 16.92 19.22 20.62 14.82
#> 136 157.1 180.2 15.2 144 161 44 131 142 160 44.1 75 143
#> 21.83 15.10 14.82 22.68 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 102 1 198 142.1 74 87 146 2.1 9 143.1 62 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 112 28 121 146.1 147 65 191 33 22 84 193.1 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 64 38 11 121.1 200 75.1 162 38.1 141 146.2 34 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 47 144.1 138 122 141.1 62.1 162.1 2.2 144.2 84.1 137 142.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 118 112.1 141.2 137.1 193.2 152 98 182 46 191.1 33.2 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 165.1 22.1 21 198.1 11.1 11.2 172 119 48 95 82 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[36]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01035325 0.56342745 0.10344014
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.164521315 -0.004738735 -0.147993161
#> grade_iii, Cure model
#> 0.937209764
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 127 3.53 1 62 0 1
#> 15 22.68 1 48 0 0
#> 157 15.10 1 47 0 0
#> 133 14.65 1 57 0 0
#> 128 20.35 1 35 0 1
#> 91 5.33 1 61 0 1
#> 194 22.40 1 38 0 1
#> 96 14.54 1 33 0 1
#> 41 18.02 1 40 1 0
#> 51 18.23 1 83 0 1
#> 170 19.54 1 43 0 1
#> 23 16.92 1 61 0 0
#> 58 19.34 1 39 0 0
#> 136 21.83 1 43 0 1
#> 40 18.00 1 28 1 0
#> 187 9.92 1 39 1 0
#> 100 16.07 1 60 0 0
#> 58.1 19.34 1 39 0 0
#> 194.1 22.40 1 38 0 1
#> 164 23.60 1 76 0 1
#> 157.1 15.10 1 47 0 0
#> 96.1 14.54 1 33 0 1
#> 97 19.14 1 65 0 1
#> 158 20.14 1 74 1 0
#> 195 11.76 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 150 20.33 1 48 0 0
#> 25 6.32 1 34 1 0
#> 14.1 12.89 1 21 0 0
#> 26 15.77 1 49 0 1
#> 158.1 20.14 1 74 1 0
#> 169 22.41 1 46 0 0
#> 136.1 21.83 1 43 0 1
#> 113 22.86 1 34 0 0
#> 14.2 12.89 1 21 0 0
#> 113.1 22.86 1 34 0 0
#> 16 8.71 1 71 0 1
#> 30 17.43 1 78 0 0
#> 81 14.06 1 34 0 0
#> 37 12.52 1 57 1 0
#> 79 16.23 1 54 1 0
#> 124 9.73 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 69 23.23 1 25 0 1
#> 13 14.34 1 54 0 1
#> 195.1 11.76 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 130 16.47 1 53 0 1
#> 81.1 14.06 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 140 12.68 1 59 1 0
#> 43 12.10 1 61 0 1
#> 150.1 20.33 1 48 0 0
#> 170.1 19.54 1 43 0 1
#> 4.1 17.64 1 NA 0 1
#> 133.1 14.65 1 57 0 0
#> 169.1 22.41 1 46 0 0
#> 89 11.44 1 NA 0 0
#> 100.1 16.07 1 60 0 0
#> 179 18.63 1 42 0 0
#> 69.1 23.23 1 25 0 1
#> 45 17.42 1 54 0 1
#> 190 20.81 1 42 1 0
#> 39 15.59 1 37 0 1
#> 25.1 6.32 1 34 1 0
#> 16.1 8.71 1 71 0 1
#> 60 13.15 1 38 1 0
#> 159 10.55 1 50 0 1
#> 29 15.45 1 68 1 0
#> 153 21.33 1 55 1 0
#> 23.1 16.92 1 61 0 0
#> 5 16.43 1 51 0 1
#> 14.3 12.89 1 21 0 0
#> 125 15.65 1 67 1 0
#> 24 23.89 1 38 0 0
#> 136.2 21.83 1 43 0 1
#> 39.1 15.59 1 37 0 1
#> 52 10.42 1 52 0 1
#> 86 23.81 1 58 0 1
#> 190.1 20.81 1 42 1 0
#> 69.2 23.23 1 25 0 1
#> 127.1 3.53 1 62 0 1
#> 140.1 12.68 1 59 1 0
#> 14.4 12.89 1 21 0 0
#> 81.2 14.06 1 34 0 0
#> 50 10.02 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 23.2 16.92 1 61 0 0
#> 78 23.88 1 43 0 0
#> 139 21.49 1 63 1 0
#> 183 9.24 1 67 1 0
#> 42 12.43 1 49 0 1
#> 49 12.19 1 48 1 0
#> 90 20.94 1 50 0 1
#> 52.1 10.42 1 52 0 1
#> 76 19.22 1 54 0 1
#> 66 22.13 1 53 0 0
#> 136.3 21.83 1 43 0 1
#> 4.2 17.64 1 NA 0 1
#> 194.2 22.40 1 38 0 1
#> 123 13.00 1 44 1 0
#> 105 19.75 1 60 0 0
#> 81.3 14.06 1 34 0 0
#> 24.1 23.89 1 38 0 0
#> 99 21.19 1 38 0 1
#> 5.1 16.43 1 51 0 1
#> 30.1 17.43 1 78 0 0
#> 79.1 16.23 1 54 1 0
#> 99.1 21.19 1 38 0 1
#> 16.2 8.71 1 71 0 1
#> 8 18.43 1 32 0 0
#> 128.1 20.35 1 35 0 1
#> 44 24.00 0 56 0 0
#> 31 24.00 0 36 0 1
#> 178 24.00 0 52 1 0
#> 19 24.00 0 57 0 1
#> 83 24.00 0 6 0 0
#> 11 24.00 0 42 0 1
#> 142 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 28 24.00 0 67 1 0
#> 135 24.00 0 58 1 0
#> 102 24.00 0 49 0 0
#> 142.1 24.00 0 53 0 0
#> 147 24.00 0 76 1 0
#> 80 24.00 0 41 0 0
#> 2 24.00 0 9 0 0
#> 142.2 24.00 0 53 0 0
#> 12 24.00 0 63 0 0
#> 62.1 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 95 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 65 24.00 0 57 1 0
#> 176 24.00 0 43 0 1
#> 162 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 98 24.00 0 34 1 0
#> 163 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 132 24.00 0 55 0 0
#> 118 24.00 0 44 1 0
#> 53.1 24.00 0 32 0 1
#> 19.1 24.00 0 57 0 1
#> 148 24.00 0 61 1 0
#> 121 24.00 0 57 1 0
#> 28.1 24.00 0 67 1 0
#> 176.1 24.00 0 43 0 1
#> 38 24.00 0 31 1 0
#> 176.2 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 2.1 24.00 0 9 0 0
#> 83.1 24.00 0 6 0 0
#> 12.1 24.00 0 63 0 0
#> 147.1 24.00 0 76 1 0
#> 104 24.00 0 50 1 0
#> 1 24.00 0 23 1 0
#> 28.2 24.00 0 67 1 0
#> 103 24.00 0 56 1 0
#> 27 24.00 0 63 1 0
#> 9 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 112 24.00 0 61 0 0
#> 80.1 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 103.1 24.00 0 56 1 0
#> 120 24.00 0 68 0 1
#> 138 24.00 0 44 1 0
#> 121.1 24.00 0 57 1 0
#> 122 24.00 0 66 0 0
#> 148.1 24.00 0 61 1 0
#> 9.1 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 200.1 24.00 0 64 0 0
#> 131 24.00 0 66 0 0
#> 22.1 24.00 0 52 1 0
#> 161 24.00 0 45 0 0
#> 3 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 71.1 24.00 0 51 0 0
#> 3.2 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 67.1 24.00 0 25 0 0
#> 72 24.00 0 40 0 1
#> 142.3 24.00 0 53 0 0
#> 115 24.00 0 NA 1 0
#> 31.1 24.00 0 36 0 1
#> 46 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 142.4 24.00 0 53 0 0
#> 112.1 24.00 0 61 0 0
#> 116 24.00 0 58 0 1
#> 191 24.00 0 60 0 1
#> 126 24.00 0 48 0 0
#> 62.2 24.00 0 71 0 0
#> 196.1 24.00 0 19 0 0
#> 87 24.00 0 27 0 0
#> 74 24.00 0 43 0 1
#> 160 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.165 NA NA NA
#> 2 age, Cure model -0.00474 NA NA NA
#> 3 grade_ii, Cure model -0.148 NA NA NA
#> 4 grade_iii, Cure model 0.937 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0104 NA NA NA
#> 2 grade_ii, Survival model 0.563 NA NA NA
#> 3 grade_iii, Survival model 0.103 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.164521 -0.004739 -0.147993 0.937210
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 253.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.164521315 -0.004738735 -0.147993161 0.937209764
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01035325 0.56342745 0.10344014
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.99056702 0.29043664 0.80385325 0.81553877 0.52594404 0.98578875
#> [7] 0.33794006 0.82709118 0.65899770 0.65139990 0.58790315 0.70190123
#> [13] 0.60410457 0.39335562 0.66645299 0.95163494 0.76114987 0.60410457
#> [19] 0.33794006 0.18316967 0.80385325 0.82709118 0.62804208 0.56283871
#> [25] 0.87775791 0.54459242 0.97620507 0.87775791 0.77361082 0.56283871
#> [31] 0.30724004 0.39335562 0.25657961 0.87775791 0.25657961 0.96165141
#> [37] 0.68099640 0.84426806 0.91548848 0.74851075 0.67379758 0.20474020
#> [43] 0.83855384 0.49661081 0.72201867 0.84426806 0.90484310 0.93119711
#> [49] 0.54459242 0.58790315 0.81553877 0.30724004 0.76114987 0.63587508
#> [55] 0.20474020 0.69495329 0.50689504 0.78591568 0.97620507 0.96165141
#> [61] 0.86664101 0.93635667 0.79793497 0.45337355 0.70190123 0.73541328
#> [67] 0.87775791 0.77982429 0.06419449 0.39335562 0.78591568 0.94149186
#> [73] 0.15722231 0.50689504 0.20474020 0.99056702 0.90484310 0.87775791
#> [79] 0.84426806 0.72872987 0.70190123 0.12604770 0.44158530 0.95667615
#> [85] 0.92076005 0.92600633 0.48597948 0.94149186 0.62009273 0.37938925
#> [91] 0.39335562 0.33794006 0.87223081 0.57957699 0.84426806 0.06419449
#> [97] 0.46455026 0.73541328 0.68099640 0.74851075 0.46455026 0.96165141
#> [103] 0.64365587 0.52594404 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 127 15 157 133 128 91 194 96 41 51 170 23 58
#> 3.53 22.68 15.10 14.65 20.35 5.33 22.40 14.54 18.02 18.23 19.54 16.92 19.34
#> 136 40 187 100 58.1 194.1 164 157.1 96.1 97 158 14 150
#> 21.83 18.00 9.92 16.07 19.34 22.40 23.60 15.10 14.54 19.14 20.14 12.89 20.33
#> 25 14.1 26 158.1 169 136.1 113 14.2 113.1 16 30 81 37
#> 6.32 12.89 15.77 20.14 22.41 21.83 22.86 12.89 22.86 8.71 17.43 14.06 12.52
#> 79 134 69 13 32 130 81.1 140 43 150.1 170.1 133.1 169.1
#> 16.23 17.81 23.23 14.34 20.90 16.47 14.06 12.68 12.10 20.33 19.54 14.65 22.41
#> 100.1 179 69.1 45 190 39 25.1 16.1 60 159 29 153 23.1
#> 16.07 18.63 23.23 17.42 20.81 15.59 6.32 8.71 13.15 10.55 15.45 21.33 16.92
#> 5 14.3 125 24 136.2 39.1 52 86 190.1 69.2 127.1 140.1 14.4
#> 16.43 12.89 15.65 23.89 21.83 15.59 10.42 23.81 20.81 23.23 3.53 12.68 12.89
#> 81.2 85 23.2 78 139 183 42 49 90 52.1 76 66 136.3
#> 14.06 16.44 16.92 23.88 21.49 9.24 12.43 12.19 20.94 10.42 19.22 22.13 21.83
#> 194.2 123 105 81.3 24.1 99 5.1 30.1 79.1 99.1 16.2 8 128.1
#> 22.40 13.00 19.75 14.06 23.89 21.19 16.43 17.43 16.23 21.19 8.71 18.43 20.35
#> 44 31 178 19 83 11 142 62 28 135 102 142.1 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 2 142.2 12 62.1 200 95 193 65 176 162 22 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 163 53 132 118 53.1 19.1 148 121 28.1 176.1 38 176.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 2.1 83.1 12.1 147.1 104 1 28.2 103 27 9 67 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.1 198 103.1 120 138 121.1 122 148.1 9.1 71 200.1 131 22.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 3 3.1 71.1 3.2 196 67.1 72 142.3 31.1 46 146 142.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.1 116 191 126 62.2 196.1 87 74 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[37]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005965352 0.554803111 0.342752285
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.07528137 0.02645817 0.16140945
#> grade_iii, Cure model
#> 0.35029634
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 68 20.62 1 44 0 0
#> 58 19.34 1 39 0 0
#> 180 14.82 1 37 0 0
#> 25 6.32 1 34 1 0
#> 167 15.55 1 56 1 0
#> 76 19.22 1 54 0 1
#> 123 13.00 1 44 1 0
#> 70 7.38 1 30 1 0
#> 158 20.14 1 74 1 0
#> 134 17.81 1 47 1 0
#> 5 16.43 1 51 0 1
#> 159 10.55 1 50 0 1
#> 177 12.53 1 75 0 0
#> 61 10.12 1 36 0 1
#> 25.1 6.32 1 34 1 0
#> 153 21.33 1 55 1 0
#> 105 19.75 1 60 0 0
#> 55 19.34 1 69 0 1
#> 180.1 14.82 1 37 0 0
#> 24 23.89 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 91 5.33 1 61 0 1
#> 123.1 13.00 1 44 1 0
#> 123.2 13.00 1 44 1 0
#> 128 20.35 1 35 0 1
#> 90 20.94 1 50 0 1
#> 77 7.27 1 67 0 1
#> 170 19.54 1 43 0 1
#> 81 14.06 1 34 0 0
#> 158.1 20.14 1 74 1 0
#> 56 12.21 1 60 0 0
#> 26 15.77 1 49 0 1
#> 70.1 7.38 1 30 1 0
#> 129 23.41 1 53 1 0
#> 184 17.77 1 38 0 0
#> 175 21.91 1 43 0 0
#> 78 23.88 1 43 0 0
#> 91.1 5.33 1 61 0 1
#> 187 9.92 1 39 1 0
#> 81.1 14.06 1 34 0 0
#> 158.2 20.14 1 74 1 0
#> 57 14.46 1 45 0 1
#> 91.2 5.33 1 61 0 1
#> 76.1 19.22 1 54 0 1
#> 169 22.41 1 46 0 0
#> 14 12.89 1 21 0 0
#> 69 23.23 1 25 0 1
#> 129.1 23.41 1 53 1 0
#> 175.1 21.91 1 43 0 0
#> 181 16.46 1 45 0 1
#> 90.1 20.94 1 50 0 1
#> 81.2 14.06 1 34 0 0
#> 194 22.40 1 38 0 1
#> 157 15.10 1 47 0 0
#> 41 18.02 1 40 1 0
#> 49 12.19 1 48 1 0
#> 171 16.57 1 41 0 1
#> 139 21.49 1 63 1 0
#> 184.1 17.77 1 38 0 0
#> 155 13.08 1 26 0 0
#> 10 10.53 1 34 0 0
#> 5.1 16.43 1 51 0 1
#> 5.2 16.43 1 51 0 1
#> 134.1 17.81 1 47 1 0
#> 78.1 23.88 1 43 0 0
#> 97 19.14 1 65 0 1
#> 14.1 12.89 1 21 0 0
#> 169.1 22.41 1 46 0 0
#> 13 14.34 1 54 0 1
#> 170.1 19.54 1 43 0 1
#> 125 15.65 1 67 1 0
#> 159.1 10.55 1 50 0 1
#> 68.1 20.62 1 44 0 0
#> 77.1 7.27 1 67 0 1
#> 180.2 14.82 1 37 0 0
#> 90.2 20.94 1 50 0 1
#> 52 10.42 1 52 0 1
#> 166 19.98 1 48 0 0
#> 100 16.07 1 60 0 0
#> 23 16.92 1 61 0 0
#> 159.2 10.55 1 50 0 1
#> 179 18.63 1 42 0 0
#> 76.2 19.22 1 54 0 1
#> 92 22.92 1 47 0 1
#> 157.1 15.10 1 47 0 0
#> 57.1 14.46 1 45 0 1
#> 36 21.19 1 48 0 1
#> 155.1 13.08 1 26 0 0
#> 23.1 16.92 1 61 0 0
#> 56.1 12.21 1 60 0 0
#> 49.1 12.19 1 48 1 0
#> 134.2 17.81 1 47 1 0
#> 14.2 12.89 1 21 0 0
#> 66 22.13 1 53 0 0
#> 6 15.64 1 39 0 0
#> 86 23.81 1 58 0 1
#> 79 16.23 1 54 1 0
#> 194.1 22.40 1 38 0 1
#> 24.2 23.89 1 38 0 0
#> 197 21.60 1 69 1 0
#> 140 12.68 1 59 1 0
#> 18 15.21 1 49 1 0
#> 93 10.33 1 52 0 1
#> 57.2 14.46 1 45 0 1
#> 140.1 12.68 1 59 1 0
#> 90.3 20.94 1 50 0 1
#> 166.1 19.98 1 48 0 0
#> 52.1 10.42 1 52 0 1
#> 29 15.45 1 68 1 0
#> 60 13.15 1 38 1 0
#> 99 21.19 1 38 0 1
#> 97.1 19.14 1 65 0 1
#> 162 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 165 24.00 0 47 0 0
#> 182 24.00 0 35 0 0
#> 141 24.00 0 44 1 0
#> 182.1 24.00 0 35 0 0
#> 62 24.00 0 71 0 0
#> 137 24.00 0 45 1 0
#> 83 24.00 0 6 0 0
#> 144 24.00 0 28 0 1
#> 9 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 121 24.00 0 57 1 0
#> 109 24.00 0 48 0 0
#> 2 24.00 0 9 0 0
#> 161 24.00 0 45 0 0
#> 71 24.00 0 51 0 0
#> 9.1 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 28 24.00 0 67 1 0
#> 138 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 126 24.00 0 48 0 0
#> 148 24.00 0 61 1 0
#> 83.1 24.00 0 6 0 0
#> 73 24.00 0 NA 0 1
#> 1 24.00 0 23 1 0
#> 126.1 24.00 0 48 0 0
#> 191.1 24.00 0 60 0 1
#> 83.2 24.00 0 6 0 0
#> 71.1 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 9.2 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 74 24.00 0 43 0 1
#> 191.2 24.00 0 60 0 1
#> 83.3 24.00 0 6 0 0
#> 75 24.00 0 21 1 0
#> 115 24.00 0 NA 1 0
#> 132 24.00 0 55 0 0
#> 27 24.00 0 63 1 0
#> 144.1 24.00 0 28 0 1
#> 38 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 132.1 24.00 0 55 0 0
#> 72 24.00 0 40 0 1
#> 135 24.00 0 58 1 0
#> 126.2 24.00 0 48 0 0
#> 73.1 24.00 0 NA 0 1
#> 200 24.00 0 64 0 0
#> 71.2 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 162.1 24.00 0 51 0 0
#> 67.1 24.00 0 25 0 0
#> 135.1 24.00 0 58 1 0
#> 53 24.00 0 32 0 1
#> 87 24.00 0 27 0 0
#> 173 24.00 0 19 0 1
#> 160 24.00 0 31 1 0
#> 144.2 24.00 0 28 0 1
#> 33 24.00 0 53 0 0
#> 84 24.00 0 39 0 1
#> 162.2 24.00 0 51 0 0
#> 9.3 24.00 0 31 1 0
#> 2.1 24.00 0 9 0 0
#> 156 24.00 0 50 1 0
#> 84.1 24.00 0 39 0 1
#> 62.1 24.00 0 71 0 0
#> 144.3 24.00 0 28 0 1
#> 72.1 24.00 0 40 0 1
#> 34 24.00 0 36 0 0
#> 80 24.00 0 41 0 0
#> 12 24.00 0 63 0 0
#> 103 24.00 0 56 1 0
#> 191.3 24.00 0 60 0 1
#> 182.2 24.00 0 35 0 0
#> 72.2 24.00 0 40 0 1
#> 176.1 24.00 0 43 0 1
#> 17 24.00 0 38 0 1
#> 53.1 24.00 0 32 0 1
#> 182.3 24.00 0 35 0 0
#> 122 24.00 0 66 0 0
#> 83.4 24.00 0 6 0 0
#> 95 24.00 0 68 0 1
#> 178 24.00 0 52 1 0
#> 17.1 24.00 0 38 0 1
#> 186 24.00 0 45 1 0
#> 53.2 24.00 0 32 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.08 NA NA NA
#> 2 age, Cure model 0.0265 NA NA NA
#> 3 grade_ii, Cure model 0.161 NA NA NA
#> 4 grade_iii, Cure model 0.350 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00597 NA NA NA
#> 2 grade_ii, Survival model 0.555 NA NA NA
#> 3 grade_iii, Survival model 0.343 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.07528 0.02646 0.16141 0.35030
#>
#> Degrees of Freedom: 196 Total (i.e. Null); 193 Residual
#> Null Deviance: 269.4
#> Residual Deviance: 260.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.07528137 0.02645817 0.16140945 0.35029634
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005965352 0.554803111 0.342752285
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.234978191 0.332605079 0.609456506 0.956488538 0.564836470 0.350622356
#> [7] 0.725714517 0.921344700 0.261885023 0.413503874 0.493364948 0.841252225
#> [13] 0.796543477 0.903508695 0.956488538 0.174166196 0.305600637 0.332605079
#> [19] 0.609456506 0.007954745 0.007954745 0.973934290 0.725714517 0.725714517
#> [25] 0.252838131 0.201186213 0.938907515 0.314720782 0.671854780 0.261885023
#> [31] 0.805501224 0.537863956 0.921344700 0.056743710 0.439620277 0.136904249
#> [37] 0.027888134 0.973934290 0.912443262 0.671854780 0.261885023 0.636196789
#> [43] 0.973934290 0.350622356 0.092179649 0.752202220 0.074151456 0.056743710
#> [49] 0.136904249 0.484337250 0.201186213 0.671854780 0.110074400 0.591652663
#> [55] 0.404423565 0.823436465 0.475296558 0.164827526 0.439620277 0.707722584
#> [61] 0.867795797 0.493364948 0.493364948 0.413503874 0.027888134 0.377256821
#> [67] 0.752202220 0.092179649 0.662850826 0.314720782 0.546861250 0.841252225
#> [73] 0.234978191 0.938907515 0.609456506 0.201186213 0.876752368 0.287790049
#> [79] 0.528858872 0.457352280 0.841252225 0.395266810 0.350622356 0.083196474
#> [85] 0.591652663 0.636196789 0.183379308 0.707722584 0.457352280 0.805501224
#> [91] 0.823436465 0.413503874 0.752202220 0.127624998 0.555833776 0.046337086
#> [97] 0.519899689 0.110074400 0.007954745 0.155384161 0.778800289 0.582748774
#> [103] 0.894562048 0.636196789 0.778800289 0.201186213 0.287790049 0.876752368
#> [109] 0.573803863 0.698701876 0.183379308 0.377256821 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 68 58 180 25 167 76 123 70 158 134 5 159 177
#> 20.62 19.34 14.82 6.32 15.55 19.22 13.00 7.38 20.14 17.81 16.43 10.55 12.53
#> 61 25.1 153 105 55 180.1 24 24.1 91 123.1 123.2 128 90
#> 10.12 6.32 21.33 19.75 19.34 14.82 23.89 23.89 5.33 13.00 13.00 20.35 20.94
#> 77 170 81 158.1 56 26 70.1 129 184 175 78 91.1 187
#> 7.27 19.54 14.06 20.14 12.21 15.77 7.38 23.41 17.77 21.91 23.88 5.33 9.92
#> 81.1 158.2 57 91.2 76.1 169 14 69 129.1 175.1 181 90.1 81.2
#> 14.06 20.14 14.46 5.33 19.22 22.41 12.89 23.23 23.41 21.91 16.46 20.94 14.06
#> 194 157 41 49 171 139 184.1 155 10 5.1 5.2 134.1 78.1
#> 22.40 15.10 18.02 12.19 16.57 21.49 17.77 13.08 10.53 16.43 16.43 17.81 23.88
#> 97 14.1 169.1 13 170.1 125 159.1 68.1 77.1 180.2 90.2 52 166
#> 19.14 12.89 22.41 14.34 19.54 15.65 10.55 20.62 7.27 14.82 20.94 10.42 19.98
#> 100 23 159.2 179 76.2 92 157.1 57.1 36 155.1 23.1 56.1 49.1
#> 16.07 16.92 10.55 18.63 19.22 22.92 15.10 14.46 21.19 13.08 16.92 12.21 12.19
#> 134.2 14.2 66 6 86 79 194.1 24.2 197 140 18 93 57.2
#> 17.81 12.89 22.13 15.64 23.81 16.23 22.40 23.89 21.60 12.68 15.21 10.33 14.46
#> 140.1 90.3 166.1 52.1 29 60 99 97.1 162 191 165 182 141
#> 12.68 20.94 19.98 10.42 15.45 13.15 21.19 19.14 24.00 24.00 24.00 24.00 24.00
#> 182.1 62 137 83 144 9 67 121 109 2 161 71 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 28 138 82 126 148 83.1 1 126.1 191.1 83.2 71.1 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.2 198.1 74 191.2 83.3 75 132 27 144.1 38 46 132.1 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 126.2 200 71.2 176 162.1 67.1 135.1 53 87 173 160 144.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 84 162.2 9.3 2.1 156 84.1 62.1 144.3 72.1 34 80 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 191.3 182.2 72.2 176.1 17 53.1 182.3 122 83.4 95 178 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 53.2
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[38]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002236192 0.579286862 0.421715194
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.066756278 0.004707428 -0.181796525
#> grade_iii, Cure model
#> 0.370019444
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 8 18.43 1 32 0 0
#> 101 9.97 1 10 0 1
#> 91 5.33 1 61 0 1
#> 85 16.44 1 36 0 0
#> 55 19.34 1 69 0 1
#> 154 12.63 1 20 1 0
#> 110 17.56 1 65 0 1
#> 63 22.77 1 31 1 0
#> 43 12.10 1 61 0 1
#> 52 10.42 1 52 0 1
#> 61 10.12 1 36 0 1
#> 133 14.65 1 57 0 0
#> 195 11.76 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 57 14.46 1 45 0 1
#> 93 10.33 1 52 0 1
#> 90 20.94 1 50 0 1
#> 155 13.08 1 26 0 0
#> 189 10.51 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 52.1 10.42 1 52 0 1
#> 69 23.23 1 25 0 1
#> 133.1 14.65 1 57 0 0
#> 15 22.68 1 48 0 0
#> 91.1 5.33 1 61 0 1
#> 107 11.18 1 54 1 0
#> 63.1 22.77 1 31 1 0
#> 194 22.40 1 38 0 1
#> 23 16.92 1 61 0 0
#> 177 12.53 1 75 0 0
#> 30 17.43 1 78 0 0
#> 189.1 10.51 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 169 22.41 1 46 0 0
#> 18 15.21 1 49 1 0
#> 45 17.42 1 54 0 1
#> 157 15.10 1 47 0 0
#> 188 16.16 1 46 0 1
#> 61.1 10.12 1 36 0 1
#> 49 12.19 1 48 1 0
#> 179 18.63 1 42 0 0
#> 70 7.38 1 30 1 0
#> 125 15.65 1 67 1 0
#> 99 21.19 1 38 0 1
#> 124 9.73 1 NA 1 0
#> 85.1 16.44 1 36 0 0
#> 23.1 16.92 1 61 0 0
#> 52.2 10.42 1 52 0 1
#> 190 20.81 1 42 1 0
#> 170 19.54 1 43 0 1
#> 157.1 15.10 1 47 0 0
#> 153 21.33 1 55 1 0
#> 16 8.71 1 71 0 1
#> 187 9.92 1 39 1 0
#> 170.1 19.54 1 43 0 1
#> 57.1 14.46 1 45 0 1
#> 37 12.52 1 57 1 0
#> 24 23.89 1 38 0 0
#> 184 17.77 1 38 0 0
#> 168 23.72 1 70 0 0
#> 175 21.91 1 43 0 0
#> 42 12.43 1 49 0 1
#> 60 13.15 1 38 1 0
#> 81 14.06 1 34 0 0
#> 140 12.68 1 59 1 0
#> 93.1 10.33 1 52 0 1
#> 32 20.90 1 37 1 0
#> 111 17.45 1 47 0 1
#> 188.1 16.16 1 46 0 1
#> 149 8.37 1 33 1 0
#> 167 15.55 1 56 1 0
#> 14 12.89 1 21 0 0
#> 107.1 11.18 1 54 1 0
#> 15.1 22.68 1 48 0 0
#> 18.1 15.21 1 49 1 0
#> 145.1 10.07 1 65 1 0
#> 128 20.35 1 35 0 1
#> 167.1 15.55 1 56 1 0
#> 154.1 12.63 1 20 1 0
#> 181 16.46 1 45 0 1
#> 192 16.44 1 31 1 0
#> 79 16.23 1 54 1 0
#> 170.2 19.54 1 43 0 1
#> 168.1 23.72 1 70 0 0
#> 157.2 15.10 1 47 0 0
#> 16.1 8.71 1 71 0 1
#> 97 19.14 1 65 0 1
#> 8.1 18.43 1 32 0 0
#> 149.1 8.37 1 33 1 0
#> 101.1 9.97 1 10 0 1
#> 45.1 17.42 1 54 0 1
#> 86 23.81 1 58 0 1
#> 125.1 15.65 1 67 1 0
#> 18.2 15.21 1 49 1 0
#> 166 19.98 1 48 0 0
#> 168.2 23.72 1 70 0 0
#> 175.1 21.91 1 43 0 0
#> 188.2 16.16 1 46 0 1
#> 10 10.53 1 34 0 0
#> 192.1 16.44 1 31 1 0
#> 30.1 17.43 1 78 0 0
#> 14.1 12.89 1 21 0 0
#> 101.2 9.97 1 10 0 1
#> 90.1 20.94 1 50 0 1
#> 39 15.59 1 37 0 1
#> 127 3.53 1 62 0 1
#> 134 17.81 1 47 1 0
#> 56 12.21 1 60 0 0
#> 110.1 17.56 1 65 0 1
#> 50 10.02 1 NA 1 0
#> 10.1 10.53 1 34 0 0
#> 194.1 22.40 1 38 0 1
#> 67 24.00 0 25 0 0
#> 138 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 64 24.00 0 43 0 0
#> 46 24.00 0 71 0 0
#> 172 24.00 0 41 0 0
#> 193 24.00 0 45 0 1
#> 46.1 24.00 0 71 0 0
#> 102 24.00 0 49 0 0
#> 28 24.00 0 67 1 0
#> 17 24.00 0 38 0 1
#> 34 24.00 0 36 0 0
#> 48 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 200 24.00 0 64 0 0
#> 33 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 7 24.00 0 37 1 0
#> 31 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 48.1 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 191 24.00 0 60 0 1
#> 148 24.00 0 61 1 0
#> 147 24.00 0 76 1 0
#> 141 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 1 24.00 0 23 1 0
#> 142 24.00 0 53 0 0
#> 11 24.00 0 42 0 1
#> 65.1 24.00 0 57 1 0
#> 98 24.00 0 34 1 0
#> 74 24.00 0 43 0 1
#> 141.1 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 75.1 24.00 0 21 1 0
#> 176 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 112.1 24.00 0 61 0 0
#> 116 24.00 0 58 0 1
#> 120 24.00 0 68 0 1
#> 102.1 24.00 0 49 0 0
#> 82 24.00 0 34 0 0
#> 144 24.00 0 28 0 1
#> 73 24.00 0 NA 0 1
#> 103 24.00 0 56 1 0
#> 87 24.00 0 27 0 0
#> 118 24.00 0 44 1 0
#> 193.1 24.00 0 45 0 1
#> 1.1 24.00 0 23 1 0
#> 28.1 24.00 0 67 1 0
#> 162 24.00 0 51 0 0
#> 21.1 24.00 0 47 0 0
#> 138.1 24.00 0 44 1 0
#> 73.1 24.00 0 NA 0 1
#> 72 24.00 0 40 0 1
#> 119 24.00 0 17 0 0
#> 71 24.00 0 51 0 0
#> 74.1 24.00 0 43 0 1
#> 28.2 24.00 0 67 1 0
#> 17.1 24.00 0 38 0 1
#> 152 24.00 0 36 0 1
#> 193.2 24.00 0 45 0 1
#> 191.1 24.00 0 60 0 1
#> 173 24.00 0 19 0 1
#> 44.1 24.00 0 56 0 0
#> 176.1 24.00 0 43 0 1
#> 28.3 24.00 0 67 1 0
#> 84 24.00 0 39 0 1
#> 178 24.00 0 52 1 0
#> 165 24.00 0 47 0 0
#> 74.2 24.00 0 43 0 1
#> 28.4 24.00 0 67 1 0
#> 62 24.00 0 71 0 0
#> 2 24.00 0 9 0 0
#> 38 24.00 0 31 1 0
#> 200.1 24.00 0 64 0 0
#> 156 24.00 0 50 1 0
#> 48.2 24.00 0 31 1 0
#> 141.2 24.00 0 44 1 0
#> 176.2 24.00 0 43 0 1
#> 200.2 24.00 0 64 0 0
#> 47 24.00 0 38 0 1
#> 182 24.00 0 35 0 0
#> 103.1 24.00 0 56 1 0
#> 144.1 24.00 0 28 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0668 NA NA NA
#> 2 age, Cure model 0.00471 NA NA NA
#> 3 grade_ii, Cure model -0.182 NA NA NA
#> 4 grade_iii, Cure model 0.370 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00224 NA NA NA
#> 2 grade_ii, Survival model 0.579 NA NA NA
#> 3 grade_iii, Survival model 0.422 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.066756 0.004707 -0.181797 0.370019
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.3
#> Residual Deviance: 262.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.066756278 0.004707428 -0.181796525 0.370019444
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002236192 0.579286862 0.421715194
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.37522452 0.91228796 0.97838102 0.50609679 0.33675858 0.74935458
#> [7] 0.41346630 0.10331627 0.80502165 0.84390263 0.88210850 0.66762152
#> [13] 0.89726716 0.68410100 0.86684317 0.24582432 0.71681201 0.21143284
#> [19] 0.84390263 0.08807326 0.66762152 0.12726025 0.97838102 0.81289357
#> [25] 0.10331627 0.16453849 0.47840985 0.76526836 0.44144277 0.33675858
#> [31] 0.15168451 0.61872612 0.46005663 0.64312741 0.55028112 0.88210850
#> [37] 0.79712423 0.36556642 0.97111557 0.57621888 0.23462193 0.50609679
#> [43] 0.47840985 0.84390263 0.27758330 0.30823502 0.64312741 0.22320136
#> [49] 0.94187039 0.93445853 0.30823502 0.68410100 0.77327999 0.01022176
#> [55] 0.40390366 0.04728274 0.18784978 0.78124448 0.70865204 0.70043155
#> [61] 0.74123244 0.86684317 0.26703397 0.43209941 0.55028112 0.95656649
#> [67] 0.60195055 0.72497724 0.81289357 0.12726025 0.61872612 0.89726716
#> [73] 0.28788802 0.60195055 0.74935458 0.49685338 0.50609679 0.54133485
#> [79] 0.30823502 0.04728274 0.64312741 0.94187039 0.35593117 0.37522452
#> [85] 0.95656649 0.91228796 0.46005663 0.03036252 0.57621888 0.61872612
#> [91] 0.29804384 0.04728274 0.18784978 0.55028112 0.82838747 0.50609679
#> [97] 0.44144277 0.72497724 0.91228796 0.24582432 0.59336505 0.99278758
#> [103] 0.39435945 0.78917934 0.41346630 0.82838747 0.16453849 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 8 101 91 85 55 154 110 63 43 52 61 133 145
#> 18.43 9.97 5.33 16.44 19.34 12.63 17.56 22.77 12.10 10.42 10.12 14.65 10.07
#> 57 93 90 155 139 52.1 69 133.1 15 91.1 107 63.1 194
#> 14.46 10.33 20.94 13.08 21.49 10.42 23.23 14.65 22.68 5.33 11.18 22.77 22.40
#> 23 177 30 58 169 18 45 157 188 61.1 49 179 70
#> 16.92 12.53 17.43 19.34 22.41 15.21 17.42 15.10 16.16 10.12 12.19 18.63 7.38
#> 125 99 85.1 23.1 52.2 190 170 157.1 153 16 187 170.1 57.1
#> 15.65 21.19 16.44 16.92 10.42 20.81 19.54 15.10 21.33 8.71 9.92 19.54 14.46
#> 37 24 184 168 175 42 60 81 140 93.1 32 111 188.1
#> 12.52 23.89 17.77 23.72 21.91 12.43 13.15 14.06 12.68 10.33 20.90 17.45 16.16
#> 149 167 14 107.1 15.1 18.1 145.1 128 167.1 154.1 181 192 79
#> 8.37 15.55 12.89 11.18 22.68 15.21 10.07 20.35 15.55 12.63 16.46 16.44 16.23
#> 170.2 168.1 157.2 16.1 97 8.1 149.1 101.1 45.1 86 125.1 18.2 166
#> 19.54 23.72 15.10 8.71 19.14 18.43 8.37 9.97 17.42 23.81 15.65 15.21 19.98
#> 168.2 175.1 188.2 10 192.1 30.1 14.1 101.2 90.1 39 127 134 56
#> 23.72 21.91 16.16 10.53 16.44 17.43 12.89 9.97 20.94 15.59 3.53 17.81 12.21
#> 110.1 10.1 194.1 67 138 21 64 46 172 193 46.1 102 28
#> 17.56 10.53 22.40 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 34 48 65 200 33 198 7 31 132 48.1 185 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 191 148 147 141 174 1 142 11 65.1 98 74 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 75.1 176 112 112.1 116 120 102.1 82 144 103 87 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 1.1 28.1 162 21.1 138.1 72 119 71 74.1 28.2 17.1 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.2 191.1 173 44.1 176.1 28.3 84 178 165 74.2 28.4 62 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 200.1 156 48.2 141.2 176.2 200.2 47 182 103.1 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[39]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005956469 1.002561769 0.615284864
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.317061771 0.004819835 0.361984572
#> grade_iii, Cure model
#> 0.630596062
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 157 15.10 1 47 0 0
#> 127 3.53 1 62 0 1
#> 124 9.73 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 26 15.77 1 49 0 1
#> 140 12.68 1 59 1 0
#> 70 7.38 1 30 1 0
#> 30 17.43 1 78 0 0
#> 68 20.62 1 44 0 0
#> 184 17.77 1 38 0 0
#> 57 14.46 1 45 0 1
#> 128 20.35 1 35 0 1
#> 56 12.21 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 30.1 17.43 1 78 0 0
#> 105 19.75 1 60 0 0
#> 133 14.65 1 57 0 0
#> 140.1 12.68 1 59 1 0
#> 140.2 12.68 1 59 1 0
#> 40.1 18.00 1 28 1 0
#> 29 15.45 1 68 1 0
#> 179 18.63 1 42 0 0
#> 101 9.97 1 10 0 1
#> 58 19.34 1 39 0 0
#> 91 5.33 1 61 0 1
#> 79 16.23 1 54 1 0
#> 192 16.44 1 31 1 0
#> 154 12.63 1 20 1 0
#> 10 10.53 1 34 0 0
#> 68.1 20.62 1 44 0 0
#> 169 22.41 1 46 0 0
#> 76 19.22 1 54 0 1
#> 60 13.15 1 38 1 0
#> 153 21.33 1 55 1 0
#> 189 10.51 1 NA 1 0
#> 57.1 14.46 1 45 0 1
#> 140.3 12.68 1 59 1 0
#> 51 18.23 1 83 0 1
#> 187 9.92 1 39 1 0
#> 101.1 9.97 1 10 0 1
#> 68.2 20.62 1 44 0 0
#> 25 6.32 1 34 1 0
#> 183 9.24 1 67 1 0
#> 128.1 20.35 1 35 0 1
#> 96 14.54 1 33 0 1
#> 93 10.33 1 52 0 1
#> 91.1 5.33 1 61 0 1
#> 187.1 9.92 1 39 1 0
#> 159 10.55 1 50 0 1
#> 90 20.94 1 50 0 1
#> 96.1 14.54 1 33 0 1
#> 57.2 14.46 1 45 0 1
#> 105.1 19.75 1 60 0 0
#> 106 16.67 1 49 1 0
#> 93.1 10.33 1 52 0 1
#> 8.1 18.43 1 32 0 0
#> 100 16.07 1 60 0 0
#> 70.1 7.38 1 30 1 0
#> 107 11.18 1 54 1 0
#> 153.1 21.33 1 55 1 0
#> 117 17.46 1 26 0 1
#> 15 22.68 1 48 0 0
#> 30.2 17.43 1 78 0 0
#> 192.1 16.44 1 31 1 0
#> 96.2 14.54 1 33 0 1
#> 77 7.27 1 67 0 1
#> 90.1 20.94 1 50 0 1
#> 90.2 20.94 1 50 0 1
#> 32 20.90 1 37 1 0
#> 49 12.19 1 48 1 0
#> 93.2 10.33 1 52 0 1
#> 155 13.08 1 26 0 0
#> 55 19.34 1 69 0 1
#> 39 15.59 1 37 0 1
#> 37 12.52 1 57 1 0
#> 169.1 22.41 1 46 0 0
#> 52 10.42 1 52 0 1
#> 149 8.37 1 33 1 0
#> 106.1 16.67 1 49 1 0
#> 85 16.44 1 36 0 0
#> 68.3 20.62 1 44 0 0
#> 154.1 12.63 1 20 1 0
#> 10.1 10.53 1 34 0 0
#> 134 17.81 1 47 1 0
#> 180 14.82 1 37 0 0
#> 92 22.92 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 110 17.56 1 65 0 1
#> 24 23.89 1 38 0 0
#> 192.2 16.44 1 31 1 0
#> 89 11.44 1 NA 0 0
#> 70.2 7.38 1 30 1 0
#> 39.1 15.59 1 37 0 1
#> 97 19.14 1 65 0 1
#> 140.4 12.68 1 59 1 0
#> 125 15.65 1 67 1 0
#> 171 16.57 1 41 0 1
#> 111 17.45 1 47 0 1
#> 140.5 12.68 1 59 1 0
#> 66 22.13 1 53 0 0
#> 6 15.64 1 39 0 0
#> 130 16.47 1 53 0 1
#> 59 10.16 1 NA 1 0
#> 55.1 19.34 1 69 0 1
#> 100.1 16.07 1 60 0 0
#> 25.1 6.32 1 34 1 0
#> 166 19.98 1 48 0 0
#> 66.1 22.13 1 53 0 0
#> 199 19.81 1 NA 0 1
#> 195.1 11.76 1 NA 1 0
#> 66.2 22.13 1 53 0 0
#> 1 24.00 0 23 1 0
#> 173 24.00 0 19 0 1
#> 143 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 82 24.00 0 34 0 0
#> 116 24.00 0 58 0 1
#> 17 24.00 0 38 0 1
#> 162 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 21 24.00 0 47 0 0
#> 17.1 24.00 0 38 0 1
#> 143.1 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 17.2 24.00 0 38 0 1
#> 75.1 24.00 0 21 1 0
#> 147 24.00 0 76 1 0
#> 143.2 24.00 0 51 0 0
#> 173.1 24.00 0 19 0 1
#> 152 24.00 0 36 0 1
#> 118.1 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 65 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 98 24.00 0 34 1 0
#> 21.1 24.00 0 47 0 0
#> 67 24.00 0 25 0 0
#> 163 24.00 0 66 0 0
#> 162.1 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 148 24.00 0 61 1 0
#> 151 24.00 0 42 0 0
#> 9 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 38 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 35.1 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 83 24.00 0 6 0 0
#> 19 24.00 0 57 0 1
#> 33 24.00 0 53 0 0
#> 94 24.00 0 51 0 1
#> 162.2 24.00 0 51 0 0
#> 33.1 24.00 0 53 0 0
#> 176 24.00 0 43 0 1
#> 142 24.00 0 53 0 0
#> 141 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 74.1 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 27.1 24.00 0 63 1 0
#> 9.1 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 131 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 67.1 24.00 0 25 0 0
#> 200 24.00 0 64 0 0
#> 126 24.00 0 48 0 0
#> 147.1 24.00 0 76 1 0
#> 27.2 24.00 0 63 1 0
#> 9.2 24.00 0 31 1 0
#> 75.2 24.00 0 21 1 0
#> 9.3 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 122 24.00 0 66 0 0
#> 11.1 24.00 0 42 0 1
#> 87 24.00 0 27 0 0
#> 182 24.00 0 35 0 0
#> 132 24.00 0 55 0 0
#> 141.1 24.00 0 44 1 0
#> 38.1 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 71 24.00 0 51 0 0
#> 115.1 24.00 0 NA 1 0
#> 112 24.00 0 61 0 0
#> 73 24.00 0 NA 0 1
#> 35.2 24.00 0 51 0 0
#> 73.1 24.00 0 NA 0 1
#> 71.1 24.00 0 51 0 0
#> 71.2 24.00 0 51 0 0
#> 53 24.00 0 32 0 1
#> 27.3 24.00 0 63 1 0
#> 162.3 24.00 0 51 0 0
#> 116.1 24.00 0 58 0 1
#> 116.2 24.00 0 58 0 1
#> 3 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 165 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.317 NA NA NA
#> 2 age, Cure model 0.00482 NA NA NA
#> 3 grade_ii, Cure model 0.362 NA NA NA
#> 4 grade_iii, Cure model 0.631 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00596 NA NA NA
#> 2 grade_ii, Survival model 1.00 NA NA NA
#> 3 grade_iii, Survival model 0.615 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.31706 0.00482 0.36198 0.63060
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.5
#> Residual Deviance: 255.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.317061771 0.004819835 0.361984572 0.630596062
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005956469 1.002561769 0.615284864
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.657874540 0.993291576 0.365896133 0.604634961 0.751956396 0.939094395
#> [7] 0.472212585 0.198345559 0.431198167 0.709891162 0.242336268 0.821226803
#> [13] 0.399892852 0.472212585 0.275762081 0.675437035 0.751956396 0.751956396
#> [19] 0.399892852 0.649133188 0.354549702 0.895953558 0.298612647 0.979894888
#> [25] 0.577565095 0.541811659 0.798277913 0.851449395 0.198345559 0.051389316
#> [31] 0.331920989 0.735141213 0.126193383 0.709891162 0.751956396 0.388476769
#> [37] 0.910545879 0.895953558 0.198345559 0.966445521 0.924871815 0.242336268
#> [43] 0.684262800 0.873888472 0.979894888 0.910545879 0.843963914 0.152442485
#> [49] 0.684262800 0.709891162 0.275762081 0.502588382 0.873888472 0.365896133
#> [55] 0.586579390 0.939094395 0.836453544 0.126193383 0.451917077 0.036602711
#> [61] 0.472212585 0.541811659 0.684262800 0.959579764 0.152442485 0.152442485
#> [67] 0.186943535 0.828876800 0.873888472 0.743541984 0.298612647 0.631576208
#> [73] 0.813598160 0.051389316 0.866402543 0.932016716 0.502588382 0.541811659
#> [79] 0.198345559 0.798277913 0.851449395 0.420858064 0.666644348 0.023213101
#> [85] 0.441588750 0.006624054 0.541811659 0.939094395 0.631576208 0.343283099
#> [91] 0.751956396 0.613679217 0.522221252 0.462109214 0.751956396 0.080404777
#> [97] 0.622614382 0.532047948 0.298612647 0.586579390 0.966445521 0.264379827
#> [103] 0.080404777 0.080404777 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 157 127 8 26 140 70 30 68 184 57 128 56 40
#> 15.10 3.53 18.43 15.77 12.68 7.38 17.43 20.62 17.77 14.46 20.35 12.21 18.00
#> 30.1 105 133 140.1 140.2 40.1 29 179 101 58 91 79 192
#> 17.43 19.75 14.65 12.68 12.68 18.00 15.45 18.63 9.97 19.34 5.33 16.23 16.44
#> 154 10 68.1 169 76 60 153 57.1 140.3 51 187 101.1 68.2
#> 12.63 10.53 20.62 22.41 19.22 13.15 21.33 14.46 12.68 18.23 9.92 9.97 20.62
#> 25 183 128.1 96 93 91.1 187.1 159 90 96.1 57.2 105.1 106
#> 6.32 9.24 20.35 14.54 10.33 5.33 9.92 10.55 20.94 14.54 14.46 19.75 16.67
#> 93.1 8.1 100 70.1 107 153.1 117 15 30.2 192.1 96.2 77 90.1
#> 10.33 18.43 16.07 7.38 11.18 21.33 17.46 22.68 17.43 16.44 14.54 7.27 20.94
#> 90.2 32 49 93.2 155 55 39 37 169.1 52 149 106.1 85
#> 20.94 20.90 12.19 10.33 13.08 19.34 15.59 12.52 22.41 10.42 8.37 16.67 16.44
#> 68.3 154.1 10.1 134 180 92 110 24 192.2 70.2 39.1 97 140.4
#> 20.62 12.63 10.53 17.81 14.82 22.92 17.56 23.89 16.44 7.38 15.59 19.14 12.68
#> 125 171 111 140.5 66 6 130 55.1 100.1 25.1 166 66.1 66.2
#> 15.65 16.57 17.45 12.68 22.13 15.64 16.47 19.34 16.07 6.32 19.98 22.13 22.13
#> 1 173 143 75 82 116 17 162 120 21 17.1 143.1 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.2 75.1 147 143.2 173.1 152 118.1 119 65 35 72 98 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 163 162.1 74 148 151 9 146 38 12 35.1 27 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 33 94 162.2 33.1 176 142 141 11 74.1 172 27.1 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 131 191 67.1 200 126 147.1 27.2 9.2 75.2 9.3 198 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 87 182 132 141.1 38.1 71 112 35.2 71.1 71.2 53 27.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.3 116.1 116.2 3 121 165
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[40]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01133765 0.25282213 0.18011908
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.795512938 0.007810368 0.570866178
#> grade_iii, Cure model
#> 1.259308823
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 92 22.92 1 47 0 1
#> 105 19.75 1 60 0 0
#> 69 23.23 1 25 0 1
#> 124 9.73 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 159 10.55 1 50 0 1
#> 197 21.60 1 69 1 0
#> 157 15.10 1 47 0 0
#> 110 17.56 1 65 0 1
#> 70 7.38 1 30 1 0
#> 4 17.64 1 NA 0 1
#> 23 16.92 1 61 0 0
#> 169 22.41 1 46 0 0
#> 14 12.89 1 21 0 0
#> 90 20.94 1 50 0 1
#> 5 16.43 1 51 0 1
#> 32 20.90 1 37 1 0
#> 91 5.33 1 61 0 1
#> 41 18.02 1 40 1 0
#> 57 14.46 1 45 0 1
#> 130 16.47 1 53 0 1
#> 69.1 23.23 1 25 0 1
#> 77 7.27 1 67 0 1
#> 177 12.53 1 75 0 0
#> 93 10.33 1 52 0 1
#> 91.1 5.33 1 61 0 1
#> 91.2 5.33 1 61 0 1
#> 52 10.42 1 52 0 1
#> 187 9.92 1 39 1 0
#> 114 13.68 1 NA 0 0
#> 113 22.86 1 34 0 0
#> 171 16.57 1 41 0 1
#> 16 8.71 1 71 0 1
#> 157.1 15.10 1 47 0 0
#> 15 22.68 1 48 0 0
#> 61 10.12 1 36 0 1
#> 61.1 10.12 1 36 0 1
#> 63 22.77 1 31 1 0
#> 70.1 7.38 1 30 1 0
#> 43 12.10 1 61 0 1
#> 150 20.33 1 48 0 0
#> 133 14.65 1 57 0 0
#> 68 20.62 1 44 0 0
#> 154 12.63 1 20 1 0
#> 153 21.33 1 55 1 0
#> 92.1 22.92 1 47 0 1
#> 49 12.19 1 48 1 0
#> 107 11.18 1 54 1 0
#> 134 17.81 1 47 1 0
#> 36 21.19 1 48 0 1
#> 192 16.44 1 31 1 0
#> 107.1 11.18 1 54 1 0
#> 41.1 18.02 1 40 1 0
#> 43.1 12.10 1 61 0 1
#> 41.2 18.02 1 40 1 0
#> 76 19.22 1 54 0 1
#> 187.1 9.92 1 39 1 0
#> 130.1 16.47 1 53 0 1
#> 26 15.77 1 49 0 1
#> 6 15.64 1 39 0 0
#> 129 23.41 1 53 1 0
#> 199 19.81 1 NA 0 1
#> 76.1 19.22 1 54 0 1
#> 36.1 21.19 1 48 0 1
#> 16.1 8.71 1 71 0 1
#> 30 17.43 1 78 0 0
#> 91.3 5.33 1 61 0 1
#> 92.2 22.92 1 47 0 1
#> 88 18.37 1 47 0 0
#> 145 10.07 1 65 1 0
#> 192.1 16.44 1 31 1 0
#> 49.1 12.19 1 48 1 0
#> 125 15.65 1 67 1 0
#> 23.1 16.92 1 61 0 0
#> 145.1 10.07 1 65 1 0
#> 128 20.35 1 35 0 1
#> 37 12.52 1 57 1 0
#> 55 19.34 1 69 0 1
#> 125.1 15.65 1 67 1 0
#> 79 16.23 1 54 1 0
#> 159.1 10.55 1 50 0 1
#> 63.1 22.77 1 31 1 0
#> 14.1 12.89 1 21 0 0
#> 175 21.91 1 43 0 0
#> 134.1 17.81 1 47 1 0
#> 188 16.16 1 46 0 1
#> 66 22.13 1 53 0 0
#> 66.1 22.13 1 53 0 0
#> 60 13.15 1 38 1 0
#> 188.1 16.16 1 46 0 1
#> 195 11.76 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 58 19.34 1 39 0 0
#> 124.1 9.73 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 49.2 12.19 1 48 1 0
#> 93.1 10.33 1 52 0 1
#> 86 23.81 1 58 0 1
#> 123 13.00 1 44 1 0
#> 117 17.46 1 26 0 1
#> 60.1 13.15 1 38 1 0
#> 129.1 23.41 1 53 1 0
#> 58.1 19.34 1 39 0 0
#> 50 10.02 1 NA 1 0
#> 76.2 19.22 1 54 0 1
#> 183 9.24 1 67 1 0
#> 23.2 16.92 1 61 0 0
#> 184 17.77 1 38 0 0
#> 130.2 16.47 1 53 0 1
#> 29 15.45 1 68 1 0
#> 60.2 13.15 1 38 1 0
#> 83 24.00 0 6 0 0
#> 198 24.00 0 66 0 1
#> 33 24.00 0 53 0 0
#> 31 24.00 0 36 0 1
#> 102 24.00 0 49 0 0
#> 162 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 109 24.00 0 48 0 0
#> 73 24.00 0 NA 0 1
#> 28 24.00 0 67 1 0
#> 143 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 118 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 141 24.00 0 44 1 0
#> 33.1 24.00 0 53 0 0
#> 104 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 54 24.00 0 53 1 0
#> 98 24.00 0 34 1 0
#> 20 24.00 0 46 1 0
#> 53 24.00 0 32 0 1
#> 87 24.00 0 27 0 0
#> 165 24.00 0 47 0 0
#> 160 24.00 0 31 1 0
#> 165.1 24.00 0 47 0 0
#> 65 24.00 0 57 1 0
#> 156 24.00 0 50 1 0
#> 193 24.00 0 45 0 1
#> 21 24.00 0 47 0 0
#> 46 24.00 0 71 0 0
#> 161 24.00 0 45 0 0
#> 3 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 109.1 24.00 0 48 0 0
#> 116 24.00 0 58 0 1
#> 200 24.00 0 64 0 0
#> 152 24.00 0 36 0 1
#> 28.1 24.00 0 67 1 0
#> 62 24.00 0 71 0 0
#> 120 24.00 0 68 0 1
#> 7 24.00 0 37 1 0
#> 122 24.00 0 66 0 0
#> 22.1 24.00 0 52 1 0
#> 141.1 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 143.1 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 160.1 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 3.1 24.00 0 31 1 0
#> 122.1 24.00 0 66 0 0
#> 46.1 24.00 0 71 0 0
#> 118.1 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 143.2 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 22.2 24.00 0 52 1 0
#> 141.2 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 160.2 24.00 0 31 1 0
#> 44.1 24.00 0 56 0 0
#> 28.2 24.00 0 67 1 0
#> 185 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 191 24.00 0 60 0 1
#> 121.1 24.00 0 57 1 0
#> 84.1 24.00 0 39 0 1
#> 7.1 24.00 0 37 1 0
#> 95 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 94 24.00 0 51 0 1
#> 109.2 24.00 0 48 0 0
#> 152.1 24.00 0 36 0 1
#> 176 24.00 0 43 0 1
#> 122.2 24.00 0 66 0 0
#> 131.1 24.00 0 66 0 0
#> 119 24.00 0 17 0 0
#> 143.3 24.00 0 51 0 0
#> 102.1 24.00 0 49 0 0
#> 119.1 24.00 0 17 0 0
#> 131.2 24.00 0 66 0 0
#> 152.2 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.796 NA NA NA
#> 2 age, Cure model 0.00781 NA NA NA
#> 3 grade_ii, Cure model 0.571 NA NA NA
#> 4 grade_iii, Cure model 1.26 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0113 NA NA NA
#> 2 grade_ii, Survival model 0.253 NA NA NA
#> 3 grade_iii, Survival model 0.180 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.79551 0.00781 0.57087 1.25931
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 251.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.795512938 0.007810368 0.570866178 1.259308823
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01133765 0.25282213 0.18011908
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.24022804 0.52191509 0.19740635 0.51239061 0.89763445 0.40420158
#> [7] 0.78518562 0.63762991 0.96757204 0.66008326 0.35011908 0.83189671
#> [13] 0.46138759 0.72202539 0.47194361 0.98176271 0.59087068 0.80305585
#> [19] 0.68837020 0.19740635 0.97704861 0.84896444 0.91318016 0.98176271
#> [25] 0.98176271 0.90801121 0.94334772 0.28874776 0.68129289 0.95801975
#> [31] 0.78518562 0.33532398 0.92335568 0.92335568 0.30545532 0.96757204
#> [37] 0.87643689 0.50250226 0.79711116 0.48227803 0.84327811 0.42854290
#> [43] 0.24022804 0.86018227 0.88712272 0.61453098 0.43997941 0.70865179
#> [49] 0.88712272 0.59087068 0.87643689 0.59087068 0.55761192 0.94334772
#> [55] 0.68837020 0.74807895 0.76682388 0.14839342 0.55761192 0.43997941
#> [61] 0.95801975 0.65269713 0.98176271 0.24022804 0.58252870 0.93344218
#> [67] 0.70865179 0.86018227 0.75446699 0.66008326 0.93344218 0.49247117
#> [73] 0.85460018 0.53127317 0.75446699 0.72867326 0.89763445 0.30545532
#> [79] 0.83189671 0.39100276 0.61453098 0.73523876 0.36449835 0.36449835
#> [85] 0.80895710 0.73523876 0.41666183 0.53127317 0.77299963 0.86018227
#> [91] 0.91318016 0.09627067 0.82616527 0.64519025 0.80895710 0.14839342
#> [97] 0.53127317 0.55761192 0.95314996 0.66008326 0.62993249 0.68837020
#> [103] 0.77913512 0.80895710 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 92 105 69 158 159 197 157 110 70 23 169 14 90
#> 22.92 19.75 23.23 20.14 10.55 21.60 15.10 17.56 7.38 16.92 22.41 12.89 20.94
#> 5 32 91 41 57 130 69.1 77 177 93 91.1 91.2 52
#> 16.43 20.90 5.33 18.02 14.46 16.47 23.23 7.27 12.53 10.33 5.33 5.33 10.42
#> 187 113 171 16 157.1 15 61 61.1 63 70.1 43 150 133
#> 9.92 22.86 16.57 8.71 15.10 22.68 10.12 10.12 22.77 7.38 12.10 20.33 14.65
#> 68 154 153 92.1 49 107 134 36 192 107.1 41.1 43.1 41.2
#> 20.62 12.63 21.33 22.92 12.19 11.18 17.81 21.19 16.44 11.18 18.02 12.10 18.02
#> 76 187.1 130.1 26 6 129 76.1 36.1 16.1 30 91.3 92.2 88
#> 19.22 9.92 16.47 15.77 15.64 23.41 19.22 21.19 8.71 17.43 5.33 22.92 18.37
#> 145 192.1 49.1 125 23.1 145.1 128 37 55 125.1 79 159.1 63.1
#> 10.07 16.44 12.19 15.65 16.92 10.07 20.35 12.52 19.34 15.65 16.23 10.55 22.77
#> 14.1 175 134.1 188 66 66.1 60 188.1 139 58 39 49.2 93.1
#> 12.89 21.91 17.81 16.16 22.13 22.13 13.15 16.16 21.49 19.34 15.59 12.19 10.33
#> 86 123 117 60.1 129.1 58.1 76.2 183 23.2 184 130.2 29 60.2
#> 23.81 13.00 17.46 13.15 23.41 19.34 19.22 9.24 16.92 17.77 16.47 15.45 13.15
#> 83 198 33 31 102 162 84 109 28 143 22 118 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 33.1 104 11 54 98 20 53 87 165 160 165.1 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 193 21 46 161 3 121 109.1 116 200 152 28.1 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 7 122 22.1 141.1 178 71 143.1 173 160.1 34 3.1 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1 118.1 9 44 143.2 103 22.2 141.2 38 131 160.2 44.1 28.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 146 64 191 121.1 84.1 7.1 95 132 94 109.2 152.1 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.2 131.1 119 143.3 102.1 119.1 131.2 152.2 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[41]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01145483 1.13316705 0.37822319
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.75553938 -0.01508319 -0.07613539
#> grade_iii, Cure model
#> 0.80208847
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 23 16.92 1 61 0 0
#> 100 16.07 1 60 0 0
#> 10 10.53 1 34 0 0
#> 76 19.22 1 54 0 1
#> 187 9.92 1 39 1 0
#> 89 11.44 1 NA 0 0
#> 25 6.32 1 34 1 0
#> 188 16.16 1 46 0 1
#> 45 17.42 1 54 0 1
#> 128 20.35 1 35 0 1
#> 79 16.23 1 54 1 0
#> 113 22.86 1 34 0 0
#> 167 15.55 1 56 1 0
#> 139 21.49 1 63 1 0
#> 88 18.37 1 47 0 0
#> 175 21.91 1 43 0 0
#> 150 20.33 1 48 0 0
#> 155 13.08 1 26 0 0
#> 45.1 17.42 1 54 0 1
#> 13 14.34 1 54 0 1
#> 145 10.07 1 65 1 0
#> 117 17.46 1 26 0 1
#> 10.1 10.53 1 34 0 0
#> 145.1 10.07 1 65 1 0
#> 81 14.06 1 34 0 0
#> 155.1 13.08 1 26 0 0
#> 154 12.63 1 20 1 0
#> 158 20.14 1 74 1 0
#> 149 8.37 1 33 1 0
#> 23.1 16.92 1 61 0 0
#> 60 13.15 1 38 1 0
#> 55 19.34 1 69 0 1
#> 29 15.45 1 68 1 0
#> 16 8.71 1 71 0 1
#> 6 15.64 1 39 0 0
#> 66 22.13 1 53 0 0
#> 190 20.81 1 42 1 0
#> 88.1 18.37 1 47 0 0
#> 90 20.94 1 50 0 1
#> 199 19.81 1 NA 0 1
#> 42 12.43 1 49 0 1
#> 70 7.38 1 30 1 0
#> 23.2 16.92 1 61 0 0
#> 99 21.19 1 38 0 1
#> 179 18.63 1 42 0 0
#> 179.1 18.63 1 42 0 0
#> 25.1 6.32 1 34 1 0
#> 23.3 16.92 1 61 0 0
#> 124 9.73 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 140 12.68 1 59 1 0
#> 150.1 20.33 1 48 0 0
#> 164 23.60 1 76 0 1
#> 128.1 20.35 1 35 0 1
#> 96 14.54 1 33 0 1
#> 158.1 20.14 1 74 1 0
#> 149.1 8.37 1 33 1 0
#> 113.1 22.86 1 34 0 0
#> 111 17.45 1 47 0 1
#> 99.1 21.19 1 38 0 1
#> 81.1 14.06 1 34 0 0
#> 24.1 23.89 1 38 0 0
#> 175.1 21.91 1 43 0 0
#> 169 22.41 1 46 0 0
#> 175.2 21.91 1 43 0 0
#> 117.1 17.46 1 26 0 1
#> 60.1 13.15 1 38 1 0
#> 128.2 20.35 1 35 0 1
#> 166 19.98 1 48 0 0
#> 187.1 9.92 1 39 1 0
#> 42.1 12.43 1 49 0 1
#> 114 13.68 1 NA 0 0
#> 189 10.51 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 32 20.90 1 37 1 0
#> 86 23.81 1 58 0 1
#> 154.1 12.63 1 20 1 0
#> 136 21.83 1 43 0 1
#> 4 17.64 1 NA 0 1
#> 6.1 15.64 1 39 0 0
#> 85 16.44 1 36 0 0
#> 14 12.89 1 21 0 0
#> 81.2 14.06 1 34 0 0
#> 25.2 6.32 1 34 1 0
#> 123 13.00 1 44 1 0
#> 113.2 22.86 1 34 0 0
#> 88.2 18.37 1 47 0 0
#> 100.1 16.07 1 60 0 0
#> 157 15.10 1 47 0 0
#> 188.1 16.16 1 46 0 1
#> 184 17.77 1 38 0 0
#> 29.1 15.45 1 68 1 0
#> 128.3 20.35 1 35 0 1
#> 107 11.18 1 54 1 0
#> 154.2 12.63 1 20 1 0
#> 41 18.02 1 40 1 0
#> 187.2 9.92 1 39 1 0
#> 81.3 14.06 1 34 0 0
#> 125 15.65 1 67 1 0
#> 110 17.56 1 65 0 1
#> 113.3 22.86 1 34 0 0
#> 107.1 11.18 1 54 1 0
#> 76.1 19.22 1 54 0 1
#> 113.4 22.86 1 34 0 0
#> 91 5.33 1 61 0 1
#> 158.2 20.14 1 74 1 0
#> 52 10.42 1 52 0 1
#> 159 10.55 1 50 0 1
#> 108 18.29 1 39 0 1
#> 42.2 12.43 1 49 0 1
#> 32.1 20.90 1 37 1 0
#> 10.2 10.53 1 34 0 0
#> 54 24.00 0 53 1 0
#> 73 24.00 0 NA 0 1
#> 2 24.00 0 9 0 0
#> 156 24.00 0 50 1 0
#> 141 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 132 24.00 0 55 0 0
#> 138 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 193 24.00 0 45 0 1
#> 112 24.00 0 61 0 0
#> 132.1 24.00 0 55 0 0
#> 122 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 46 24.00 0 71 0 0
#> 191 24.00 0 60 0 1
#> 11 24.00 0 42 0 1
#> 126 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 46.1 24.00 0 71 0 0
#> 161 24.00 0 45 0 0
#> 176 24.00 0 43 0 1
#> 116 24.00 0 58 0 1
#> 151 24.00 0 42 0 0
#> 143 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 174 24.00 0 49 1 0
#> 3 24.00 0 31 1 0
#> 122.1 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 143.1 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 198 24.00 0 66 0 1
#> 104 24.00 0 50 1 0
#> 185 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 54.1 24.00 0 53 1 0
#> 65 24.00 0 57 1 0
#> 2.1 24.00 0 9 0 0
#> 12 24.00 0 63 0 0
#> 191.1 24.00 0 60 0 1
#> 9 24.00 0 31 1 0
#> 72.1 24.00 0 40 0 1
#> 156.1 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 20 24.00 0 46 1 0
#> 163 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 156.2 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 142 24.00 0 53 0 0
#> 132.2 24.00 0 55 0 0
#> 144 24.00 0 28 0 1
#> 28.1 24.00 0 67 1 0
#> 132.3 24.00 0 55 0 0
#> 48 24.00 0 31 1 0
#> 20.1 24.00 0 46 1 0
#> 112.1 24.00 0 61 0 0
#> 121 24.00 0 57 1 0
#> 178.1 24.00 0 52 1 0
#> 172.1 24.00 0 41 0 0
#> 137 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 200 24.00 0 64 0 0
#> 38 24.00 0 31 1 0
#> 156.3 24.00 0 50 1 0
#> 186 24.00 0 45 1 0
#> 74 24.00 0 43 0 1
#> 46.2 24.00 0 71 0 0
#> 132.4 24.00 0 55 0 0
#> 73.1 24.00 0 NA 0 1
#> 1 24.00 0 23 1 0
#> 80 24.00 0 41 0 0
#> 103 24.00 0 56 1 0
#> 27 24.00 0 63 1 0
#> 135 24.00 0 58 1 0
#> 35.1 24.00 0 51 0 0
#> 27.1 24.00 0 63 1 0
#> 34.1 24.00 0 36 0 0
#> 196 24.00 0 19 0 0
#> 67 24.00 0 25 0 0
#> 44 24.00 0 56 0 0
#> 12.1 24.00 0 63 0 0
#> 87 24.00 0 27 0 0
#> 48.1 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.756 NA NA NA
#> 2 age, Cure model -0.0151 NA NA NA
#> 3 grade_ii, Cure model -0.0761 NA NA NA
#> 4 grade_iii, Cure model 0.802 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0115 NA NA NA
#> 2 grade_ii, Survival model 1.13 NA NA NA
#> 3 grade_iii, Survival model 0.378 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.75554 -0.01508 -0.07614 0.80209
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 256.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.75553938 -0.01508319 -0.07613539 0.80208847
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01145483 1.13316705 0.37822319
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.438324641 0.519446450 0.843824127 0.284566101 0.901220995 0.965261324
#> [7] 0.499015807 0.418757936 0.187846669 0.488752454 0.024927784 0.582327089
#> [13] 0.117588611 0.321733651 0.076198293 0.221883017 0.706600181 0.418757936
#> [19] 0.634090507 0.882163714 0.389656591 0.843824127 0.882163714 0.644526581
#> [25] 0.706600181 0.758011596 0.240229661 0.938114369 0.438324641 0.686116553
#> [31] 0.275359210 0.592812072 0.928797006 0.561307754 0.066290249 0.178734281
#> [37] 0.321733651 0.149181022 0.786568433 0.956252208 0.438324641 0.128356317
#> [43] 0.302932104 0.302932104 0.965261324 0.438324641 0.002237195 0.747797852
#> [49] 0.221883017 0.017108028 0.187846669 0.623691003 0.240229661 0.938114369
#> [55] 0.024927784 0.408956639 0.128356317 0.644526581 0.002237195 0.076198293
#> [61] 0.057014443 0.076198293 0.389656591 0.686116553 0.187846669 0.266255158
#> [67] 0.901220995 0.786568433 0.540284538 0.160124953 0.010492112 0.758011596
#> [73] 0.106295588 0.561307754 0.478341994 0.737502575 0.644526581 0.965261324
#> [79] 0.727237936 0.024927784 0.321733651 0.519446450 0.613291465 0.499015807
#> [85] 0.370106402 0.592812072 0.187846669 0.815299863 0.758011596 0.360459467
#> [91] 0.901220995 0.644526581 0.550840422 0.379842912 0.024927784 0.815299863
#> [97] 0.284566101 0.024927784 0.991241867 0.240229661 0.872483196 0.834266813
#> [103] 0.350557093 0.786568433 0.160124953 0.843824127 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 23 100 10 76 187 25 188 45 128 79 113 167 139
#> 16.92 16.07 10.53 19.22 9.92 6.32 16.16 17.42 20.35 16.23 22.86 15.55 21.49
#> 88 175 150 155 45.1 13 145 117 10.1 145.1 81 155.1 154
#> 18.37 21.91 20.33 13.08 17.42 14.34 10.07 17.46 10.53 10.07 14.06 13.08 12.63
#> 158 149 23.1 60 55 29 16 6 66 190 88.1 90 42
#> 20.14 8.37 16.92 13.15 19.34 15.45 8.71 15.64 22.13 20.81 18.37 20.94 12.43
#> 70 23.2 99 179 179.1 25.1 23.3 24 140 150.1 164 128.1 96
#> 7.38 16.92 21.19 18.63 18.63 6.32 16.92 23.89 12.68 20.33 23.60 20.35 14.54
#> 158.1 149.1 113.1 111 99.1 81.1 24.1 175.1 169 175.2 117.1 60.1 128.2
#> 20.14 8.37 22.86 17.45 21.19 14.06 23.89 21.91 22.41 21.91 17.46 13.15 20.35
#> 166 187.1 42.1 26 32 86 154.1 136 6.1 85 14 81.2 25.2
#> 19.98 9.92 12.43 15.77 20.90 23.81 12.63 21.83 15.64 16.44 12.89 14.06 6.32
#> 123 113.2 88.2 100.1 157 188.1 184 29.1 128.3 107 154.2 41 187.2
#> 13.00 22.86 18.37 16.07 15.10 16.16 17.77 15.45 20.35 11.18 12.63 18.02 9.92
#> 81.3 125 110 113.3 107.1 76.1 113.4 91 158.2 52 159 108 42.2
#> 14.06 15.65 17.56 22.86 11.18 19.22 22.86 5.33 20.14 10.42 10.55 18.29 12.43
#> 32.1 10.2 54 2 156 141 84 132 138 28 193 112 132.1
#> 20.90 10.53 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 47 46 191 11 126 83 46.1 161 176 116 151 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 172 72 174 3 122.1 22 143.1 21 198 104 185 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.1 65 2.1 12 191.1 9 72.1 156.1 33 20 163 118 156.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 142 132.2 144 28.1 132.3 48 20.1 112.1 121 178.1 172.1 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 200 38 156.3 186 74 46.2 132.4 1 80 103 27 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.1 27.1 34.1 196 67 44 12.1 87 48.1 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[42]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005538459 0.435887551 0.368230095
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.103551999 -0.002786442 0.233882736
#> grade_iii, Cure model
#> 0.550154250
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 124 9.73 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 76 19.22 1 54 0 1
#> 108 18.29 1 39 0 1
#> 181 16.46 1 45 0 1
#> 18 15.21 1 49 1 0
#> 58 19.34 1 39 0 0
#> 113 22.86 1 34 0 0
#> 5 16.43 1 51 0 1
#> 37 12.52 1 57 1 0
#> 108.1 18.29 1 39 0 1
#> 190 20.81 1 42 1 0
#> 199 19.81 1 NA 0 1
#> 37.1 12.52 1 57 1 0
#> 199.1 19.81 1 NA 0 1
#> 114 13.68 1 NA 0 0
#> 8 18.43 1 32 0 0
#> 145 10.07 1 65 1 0
#> 52 10.42 1 52 0 1
#> 68 20.62 1 44 0 0
#> 136 21.83 1 43 0 1
#> 177 12.53 1 75 0 0
#> 166 19.98 1 48 0 0
#> 111 17.45 1 47 0 1
#> 30 17.43 1 78 0 0
#> 140 12.68 1 59 1 0
#> 45 17.42 1 54 0 1
#> 8.1 18.43 1 32 0 0
#> 91 5.33 1 61 0 1
#> 184 17.77 1 38 0 0
#> 18.1 15.21 1 49 1 0
#> 154 12.63 1 20 1 0
#> 42 12.43 1 49 0 1
#> 187 9.92 1 39 1 0
#> 136.1 21.83 1 43 0 1
#> 88 18.37 1 47 0 0
#> 177.1 12.53 1 75 0 0
#> 99 21.19 1 38 0 1
#> 61 10.12 1 36 0 1
#> 66 22.13 1 53 0 0
#> 10 10.53 1 34 0 0
#> 129 23.41 1 53 1 0
#> 6 15.64 1 39 0 0
#> 32 20.90 1 37 1 0
#> 77 7.27 1 67 0 1
#> 155 13.08 1 26 0 0
#> 171 16.57 1 41 0 1
#> 195 11.76 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 63 22.77 1 31 1 0
#> 170 19.54 1 43 0 1
#> 167 15.55 1 56 1 0
#> 63.1 22.77 1 31 1 0
#> 92 22.92 1 47 0 1
#> 15 22.68 1 48 0 0
#> 8.2 18.43 1 32 0 0
#> 88.1 18.37 1 47 0 0
#> 49 12.19 1 48 1 0
#> 26 15.77 1 49 0 1
#> 127 3.53 1 62 0 1
#> 61.1 10.12 1 36 0 1
#> 18.2 15.21 1 49 1 0
#> 58.1 19.34 1 39 0 0
#> 128 20.35 1 35 0 1
#> 45.1 17.42 1 54 0 1
#> 8.3 18.43 1 32 0 0
#> 97 19.14 1 65 0 1
#> 113.1 22.86 1 34 0 0
#> 188 16.16 1 46 0 1
#> 180 14.82 1 37 0 0
#> 170.1 19.54 1 43 0 1
#> 86 23.81 1 58 0 1
#> 134 17.81 1 47 1 0
#> 57 14.46 1 45 0 1
#> 81 14.06 1 34 0 0
#> 136.2 21.83 1 43 0 1
#> 140.1 12.68 1 59 1 0
#> 177.2 12.53 1 75 0 0
#> 188.1 16.16 1 46 0 1
#> 25 6.32 1 34 1 0
#> 107 11.18 1 54 1 0
#> 106 16.67 1 49 1 0
#> 6.1 15.64 1 39 0 0
#> 10.1 10.53 1 34 0 0
#> 5.1 16.43 1 51 0 1
#> 78 23.88 1 43 0 0
#> 134.1 17.81 1 47 1 0
#> 128.1 20.35 1 35 0 1
#> 81.1 14.06 1 34 0 0
#> 68.1 20.62 1 44 0 0
#> 168 23.72 1 70 0 0
#> 179 18.63 1 42 0 0
#> 187.1 9.92 1 39 1 0
#> 43 12.10 1 61 0 1
#> 129.1 23.41 1 53 1 0
#> 101 9.97 1 10 0 1
#> 154.1 12.63 1 20 1 0
#> 169 22.41 1 46 0 0
#> 10.2 10.53 1 34 0 0
#> 45.2 17.42 1 54 0 1
#> 188.2 16.16 1 46 0 1
#> 39 15.59 1 37 0 1
#> 8.4 18.43 1 32 0 0
#> 117 17.46 1 26 0 1
#> 66.1 22.13 1 53 0 0
#> 177.3 12.53 1 75 0 0
#> 24 23.89 1 38 0 0
#> 124.1 9.73 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 150 20.33 1 48 0 0
#> 37.2 12.52 1 57 1 0
#> 117.1 17.46 1 26 0 1
#> 151 24.00 0 42 0 0
#> 48 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 2 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 44 24.00 0 56 0 0
#> 147 24.00 0 76 1 0
#> 163 24.00 0 66 0 0
#> 48.1 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 173 24.00 0 19 0 1
#> 185 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 200 24.00 0 64 0 0
#> 44.1 24.00 0 56 0 0
#> 148 24.00 0 61 1 0
#> 151.1 24.00 0 42 0 0
#> 95 24.00 0 68 0 1
#> 115 24.00 0 NA 1 0
#> 144 24.00 0 28 0 1
#> 163.1 24.00 0 66 0 0
#> 135 24.00 0 58 1 0
#> 84 24.00 0 39 0 1
#> 147.1 24.00 0 76 1 0
#> 131 24.00 0 66 0 0
#> 71 24.00 0 51 0 0
#> 198 24.00 0 66 0 1
#> 137 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 80 24.00 0 41 0 0
#> 102 24.00 0 49 0 0
#> 191 24.00 0 60 0 1
#> 31 24.00 0 36 0 1
#> 122 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 2.1 24.00 0 9 0 0
#> 131.1 24.00 0 66 0 0
#> 173.1 24.00 0 19 0 1
#> 163.2 24.00 0 66 0 0
#> 200.1 24.00 0 64 0 0
#> 182 24.00 0 35 0 0
#> 84.1 24.00 0 39 0 1
#> 3 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 3.1 24.00 0 31 1 0
#> 163.3 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 115.1 24.00 0 NA 1 0
#> 1.1 24.00 0 23 1 0
#> 178 24.00 0 52 1 0
#> 135.1 24.00 0 58 1 0
#> 191.1 24.00 0 60 0 1
#> 142 24.00 0 53 0 0
#> 152 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 65 24.00 0 57 1 0
#> 87 24.00 0 27 0 0
#> 182.1 24.00 0 35 0 0
#> 71.1 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 11.1 24.00 0 42 0 1
#> 95.1 24.00 0 68 0 1
#> 121 24.00 0 57 1 0
#> 142.1 24.00 0 53 0 0
#> 11.2 24.00 0 42 0 1
#> 62 24.00 0 71 0 0
#> 2.2 24.00 0 9 0 0
#> 178.1 24.00 0 52 1 0
#> 48.2 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 182.2 24.00 0 35 0 0
#> 147.2 24.00 0 76 1 0
#> 67 24.00 0 25 0 0
#> 152.1 24.00 0 36 0 1
#> 120 24.00 0 68 0 1
#> 71.2 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 116 24.00 0 58 0 1
#> 17 24.00 0 38 0 1
#> 102.1 24.00 0 49 0 0
#> 119 24.00 0 17 0 0
#> 47.1 24.00 0 38 0 1
#> 161 24.00 0 45 0 0
#> 28 24.00 0 67 1 0
#> 73 24.00 0 NA 0 1
#> 44.2 24.00 0 56 0 0
#> 137.1 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.104 NA NA NA
#> 2 age, Cure model -0.00279 NA NA NA
#> 3 grade_ii, Cure model 0.234 NA NA NA
#> 4 grade_iii, Cure model 0.550 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00554 NA NA NA
#> 2 grade_ii, Survival model 0.436 NA NA NA
#> 3 grade_iii, Survival model 0.368 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.103552 -0.002786 0.233883 0.550154
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.3
#> Residual Deviance: 258.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.103551999 -0.002786442 0.233882736 0.550154250
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005538459 0.435887551 0.368230095
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.48846166 0.57565052 0.68726131 0.77234957 0.46990496 0.20207590
#> [7] 0.69472211 0.87607242 0.57565052 0.36908533 0.87607242 0.51566459
#> [13] 0.95417074 0.93650203 0.37994326 0.31221647 0.85108567 0.44136003
#> [19] 0.63335497 0.64136877 0.82538017 0.64932884 0.51566459 0.98871861
#> [25] 0.60900183 0.77234957 0.83830459 0.89443839 0.96582989 0.31221647
#> [31] 0.55833523 0.85108567 0.34642228 0.94244161 0.28659313 0.91869196
#> [37] 0.15256189 0.74457169 0.35791483 0.97730851 0.81877366 0.67973068
#> [43] 0.43148321 0.23217011 0.45117001 0.76546577 0.23217011 0.18590849
#> [49] 0.25932955 0.51566459 0.55833523 0.90056495 0.73753638 0.99437590
#> [55] 0.94244161 0.77234957 0.46990496 0.40102153 0.64932884 0.51566459
#> [61] 0.49766239 0.20207590 0.70927848 0.79227448 0.45117001 0.10329802
#> [67] 0.59256217 0.79895973 0.80559754 0.31221647 0.82538017 0.85108567
#> [73] 0.70927848 0.98302791 0.91269224 0.67213156 0.74457169 0.91869196
#> [79] 0.69472211 0.06927762 0.59256217 0.40102153 0.80559754 0.37994326
#> [85] 0.12903045 0.50668443 0.96582989 0.90664940 0.15256189 0.96000965
#> [91] 0.83830459 0.27305998 0.91869196 0.64932884 0.70927848 0.75851264
#> [97] 0.51566459 0.61725163 0.28659313 0.85108567 0.03081223 0.73044043
#> [103] 0.42129635 0.87607242 0.61725163 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 76 108 181 18 58 113 5 37 108.1 190 37.1 8 145
#> 19.22 18.29 16.46 15.21 19.34 22.86 16.43 12.52 18.29 20.81 12.52 18.43 10.07
#> 52 68 136 177 166 111 30 140 45 8.1 91 184 18.1
#> 10.42 20.62 21.83 12.53 19.98 17.45 17.43 12.68 17.42 18.43 5.33 17.77 15.21
#> 154 42 187 136.1 88 177.1 99 61 66 10 129 6 32
#> 12.63 12.43 9.92 21.83 18.37 12.53 21.19 10.12 22.13 10.53 23.41 15.64 20.90
#> 77 155 171 158 63 170 167 63.1 92 15 8.2 88.1 49
#> 7.27 13.08 16.57 20.14 22.77 19.54 15.55 22.77 22.92 22.68 18.43 18.37 12.19
#> 26 127 61.1 18.2 58.1 128 45.1 8.3 97 113.1 188 180 170.1
#> 15.77 3.53 10.12 15.21 19.34 20.35 17.42 18.43 19.14 22.86 16.16 14.82 19.54
#> 86 134 57 81 136.2 140.1 177.2 188.1 25 107 106 6.1 10.1
#> 23.81 17.81 14.46 14.06 21.83 12.68 12.53 16.16 6.32 11.18 16.67 15.64 10.53
#> 5.1 78 134.1 128.1 81.1 68.1 168 179 187.1 43 129.1 101 154.1
#> 16.43 23.88 17.81 20.35 14.06 20.62 23.72 18.63 9.92 12.10 23.41 9.97 12.63
#> 169 10.2 45.2 188.2 39 8.4 117 66.1 177.3 24 100 150 37.2
#> 22.41 10.53 17.42 16.16 15.59 18.43 17.46 22.13 12.53 23.89 16.07 20.33 12.52
#> 117.1 151 48 1 2 172 44 147 163 48.1 53 173 185
#> 17.46 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 200 44.1 148 151.1 95 144 163.1 135 84 147.1 131 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 137 112 80 102 191 31 122 46 2.1 131.1 173.1 163.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.1 182 84.1 3 11 3.1 163.3 47 1.1 178 135.1 191.1 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 132 65 87 182.1 71.1 35 83 11.1 95.1 121 142.1 11.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 2.2 178.1 48.2 38 182.2 147.2 67 152.1 120 71.2 126 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 102.1 119 47.1 161 28 44.2 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[43]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004766251 0.610080863 0.389606885
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.140381275 -0.001755715 0.427018336
#> grade_iii, Cure model
#> 0.820095936
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 96 14.54 1 33 0 1
#> 189 10.51 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 37 12.52 1 57 1 0
#> 189.1 10.51 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 18 15.21 1 49 1 0
#> 58 19.34 1 39 0 0
#> 130 16.47 1 53 0 1
#> 79 16.23 1 54 1 0
#> 99 21.19 1 38 0 1
#> 51 18.23 1 83 0 1
#> 69 23.23 1 25 0 1
#> 150 20.33 1 48 0 0
#> 180 14.82 1 37 0 0
#> 149 8.37 1 33 1 0
#> 59 10.16 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 140 12.68 1 59 1 0
#> 15 22.68 1 48 0 0
#> 188 16.16 1 46 0 1
#> 5 16.43 1 51 0 1
#> 180.1 14.82 1 37 0 0
#> 192 16.44 1 31 1 0
#> 29 15.45 1 68 1 0
#> 124 9.73 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 36 21.19 1 48 0 1
#> 123 13.00 1 44 1 0
#> 70 7.38 1 30 1 0
#> 139 21.49 1 63 1 0
#> 30 17.43 1 78 0 0
#> 153 21.33 1 55 1 0
#> 97 19.14 1 65 0 1
#> 56 12.21 1 60 0 0
#> 110 17.56 1 65 0 1
#> 117 17.46 1 26 0 1
#> 192.1 16.44 1 31 1 0
#> 4 17.64 1 NA 0 1
#> 171 16.57 1 41 0 1
#> 190.1 20.81 1 42 1 0
#> 24 23.89 1 38 0 0
#> 190.2 20.81 1 42 1 0
#> 110.1 17.56 1 65 0 1
#> 145 10.07 1 65 1 0
#> 124.1 9.73 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 6 15.64 1 39 0 0
#> 153.1 21.33 1 55 1 0
#> 68 20.62 1 44 0 0
#> 55 19.34 1 69 0 1
#> 199 19.81 1 NA 0 1
#> 89 11.44 1 NA 0 0
#> 127 3.53 1 62 0 1
#> 43 12.10 1 61 0 1
#> 26 15.77 1 49 0 1
#> 57 14.46 1 45 0 1
#> 171.1 16.57 1 41 0 1
#> 127.1 3.53 1 62 0 1
#> 5.1 16.43 1 51 0 1
#> 175 21.91 1 43 0 0
#> 170 19.54 1 43 0 1
#> 30.1 17.43 1 78 0 0
#> 60 13.15 1 38 1 0
#> 167 15.55 1 56 1 0
#> 101 9.97 1 10 0 1
#> 130.1 16.47 1 53 0 1
#> 192.2 16.44 1 31 1 0
#> 93 10.33 1 52 0 1
#> 78 23.88 1 43 0 0
#> 184 17.77 1 38 0 0
#> 36.1 21.19 1 48 0 1
#> 90 20.94 1 50 0 1
#> 179 18.63 1 42 0 0
#> 154 12.63 1 20 1 0
#> 192.3 16.44 1 31 1 0
#> 130.2 16.47 1 53 0 1
#> 88 18.37 1 47 0 0
#> 92 22.92 1 47 0 1
#> 188.1 16.16 1 46 0 1
#> 10 10.53 1 34 0 0
#> 175.1 21.91 1 43 0 0
#> 133 14.65 1 57 0 0
#> 37.1 12.52 1 57 1 0
#> 190.3 20.81 1 42 1 0
#> 170.1 19.54 1 43 0 1
#> 150.1 20.33 1 48 0 0
#> 96.1 14.54 1 33 0 1
#> 4.1 17.64 1 NA 0 1
#> 166 19.98 1 48 0 0
#> 56.1 12.21 1 60 0 0
#> 51.1 18.23 1 83 0 1
#> 179.1 18.63 1 42 0 0
#> 23 16.92 1 61 0 0
#> 60.1 13.15 1 38 1 0
#> 8 18.43 1 32 0 0
#> 49 12.19 1 48 1 0
#> 39 15.59 1 37 0 1
#> 69.1 23.23 1 25 0 1
#> 140.1 12.68 1 59 1 0
#> 197 21.60 1 69 1 0
#> 41 18.02 1 40 1 0
#> 45 17.42 1 54 0 1
#> 4.2 17.64 1 NA 0 1
#> 199.1 19.81 1 NA 0 1
#> 183 9.24 1 67 1 0
#> 15.1 22.68 1 48 0 0
#> 8.1 18.43 1 32 0 0
#> 101.1 9.97 1 10 0 1
#> 107 11.18 1 54 1 0
#> 134.1 17.81 1 47 1 0
#> 76 19.22 1 54 0 1
#> 121 24.00 0 57 1 0
#> 21 24.00 0 47 0 0
#> 148 24.00 0 61 1 0
#> 135 24.00 0 58 1 0
#> 144 24.00 0 28 0 1
#> 75 24.00 0 21 1 0
#> 121.1 24.00 0 57 1 0
#> 172 24.00 0 41 0 0
#> 74 24.00 0 43 0 1
#> 28 24.00 0 67 1 0
#> 148.1 24.00 0 61 1 0
#> 143 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 102 24.00 0 49 0 0
#> 176.1 24.00 0 43 0 1
#> 65 24.00 0 57 1 0
#> 11 24.00 0 42 0 1
#> 116 24.00 0 58 0 1
#> 21.1 24.00 0 47 0 0
#> 64 24.00 0 43 0 0
#> 191 24.00 0 60 0 1
#> 65.1 24.00 0 57 1 0
#> 67 24.00 0 25 0 0
#> 162 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 152 24.00 0 36 0 1
#> 12 24.00 0 63 0 0
#> 160 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 193 24.00 0 45 0 1
#> 147 24.00 0 76 1 0
#> 44 24.00 0 56 0 0
#> 200 24.00 0 64 0 0
#> 95 24.00 0 68 0 1
#> 62 24.00 0 71 0 0
#> 152.1 24.00 0 36 0 1
#> 83 24.00 0 6 0 0
#> 20 24.00 0 46 1 0
#> 146 24.00 0 63 1 0
#> 115 24.00 0 NA 1 0
#> 53 24.00 0 32 0 1
#> 151 24.00 0 42 0 0
#> 143.1 24.00 0 51 0 0
#> 191.1 24.00 0 60 0 1
#> 141 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 34 24.00 0 36 0 0
#> 44.1 24.00 0 56 0 0
#> 54 24.00 0 53 1 0
#> 115.1 24.00 0 NA 1 0
#> 141.1 24.00 0 44 1 0
#> 176.2 24.00 0 43 0 1
#> 12.1 24.00 0 63 0 0
#> 200.1 24.00 0 64 0 0
#> 172.1 24.00 0 41 0 0
#> 7 24.00 0 37 1 0
#> 73 24.00 0 NA 0 1
#> 165 24.00 0 47 0 0
#> 193.1 24.00 0 45 0 1
#> 196 24.00 0 19 0 0
#> 102.1 24.00 0 49 0 0
#> 173 24.00 0 19 0 1
#> 46 24.00 0 71 0 0
#> 83.1 24.00 0 6 0 0
#> 82 24.00 0 34 0 0
#> 165.1 24.00 0 47 0 0
#> 17 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 132 24.00 0 55 0 0
#> 73.1 24.00 0 NA 0 1
#> 98 24.00 0 34 1 0
#> 47 24.00 0 38 0 1
#> 98.1 24.00 0 34 1 0
#> 104.1 24.00 0 50 1 0
#> 151.1 24.00 0 42 0 0
#> 12.2 24.00 0 63 0 0
#> 163.1 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 148.2 24.00 0 61 1 0
#> 135.1 24.00 0 58 1 0
#> 152.2 24.00 0 36 0 1
#> 11.1 24.00 0 42 0 1
#> 156 24.00 0 50 1 0
#> 17.1 24.00 0 38 0 1
#> 109 24.00 0 48 0 0
#> 191.2 24.00 0 60 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.140 NA NA NA
#> 2 age, Cure model -0.00176 NA NA NA
#> 3 grade_ii, Cure model 0.427 NA NA NA
#> 4 grade_iii, Cure model 0.820 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00477 NA NA NA
#> 2 grade_ii, Survival model 0.610 NA NA NA
#> 3 grade_iii, Survival model 0.390 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.140381 -0.001756 0.427018 0.820096
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 254.9
#> Residual Deviance: 249.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.140381275 -0.001755715 0.427018336 0.820095936
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004766251 0.610080863 0.389606885
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.83091190 0.98386420 0.89878320 0.59038369 0.80508785 0.47958535
#> [7] 0.68670230 0.75109070 0.32743763 0.56402667 0.11477359 0.42870942
#> [13] 0.81157576 0.97291723 0.87471914 0.88084588 0.18534581 0.75802532
#> [19] 0.73710803 0.81157576 0.70894088 0.79852993 0.37710579 0.32743763
#> [25] 0.86858789 0.97840792 0.28293358 0.63970470 0.29946405 0.50849641
#> [31] 0.91045541 0.61543556 0.63162657 0.70894088 0.67134504 0.37710579
#> [37] 0.03299731 0.37710579 0.61543556 0.95066007 0.84996173 0.77840097
#> [43] 0.29946405 0.41811881 0.47958535 0.98929116 0.92786015 0.77162353
#> [49] 0.84362222 0.67134504 0.98929116 0.73710803 0.22587336 0.45975988
#> [55] 0.63970470 0.85625851 0.79188773 0.95627166 0.68670230 0.70894088
#> [61] 0.94499805 0.07600228 0.60706155 0.32743763 0.36464094 0.51790375
#> [67] 0.89281804 0.70894088 0.68670230 0.55479197 0.16249339 0.75802532
#> [73] 0.93930561 0.22587336 0.82446014 0.89878320 0.37710579 0.45975988
#> [79] 0.42870942 0.83091190 0.44937010 0.91045541 0.56402667 0.51790375
#> [85] 0.66347810 0.85625851 0.53640007 0.92207830 0.78516639 0.11477359
#> [91] 0.88084588 0.26483331 0.58166177 0.65557956 0.96739055 0.18534581
#> [97] 0.53640007 0.95627166 0.93360710 0.59038369 0.49890949 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 96 91 37 134 18 58 130 79 99 51 69 150 180
#> 14.54 5.33 12.52 17.81 15.21 19.34 16.47 16.23 21.19 18.23 23.23 20.33 14.82
#> 149 14 140 15 188 5 180.1 192 29 190 36 123 70
#> 8.37 12.89 12.68 22.68 16.16 16.43 14.82 16.44 15.45 20.81 21.19 13.00 7.38
#> 139 30 153 97 56 110 117 192.1 171 190.1 24 190.2 110.1
#> 21.49 17.43 21.33 19.14 12.21 17.56 17.46 16.44 16.57 20.81 23.89 20.81 17.56
#> 145 13 6 153.1 68 55 127 43 26 57 171.1 127.1 5.1
#> 10.07 14.34 15.64 21.33 20.62 19.34 3.53 12.10 15.77 14.46 16.57 3.53 16.43
#> 175 170 30.1 60 167 101 130.1 192.2 93 78 184 36.1 90
#> 21.91 19.54 17.43 13.15 15.55 9.97 16.47 16.44 10.33 23.88 17.77 21.19 20.94
#> 179 154 192.3 130.2 88 92 188.1 10 175.1 133 37.1 190.3 170.1
#> 18.63 12.63 16.44 16.47 18.37 22.92 16.16 10.53 21.91 14.65 12.52 20.81 19.54
#> 150.1 96.1 166 56.1 51.1 179.1 23 60.1 8 49 39 69.1 140.1
#> 20.33 14.54 19.98 12.21 18.23 18.63 16.92 13.15 18.43 12.19 15.59 23.23 12.68
#> 197 41 45 183 15.1 8.1 101.1 107 134.1 76 121 21 148
#> 21.60 18.02 17.42 9.24 22.68 18.43 9.97 11.18 17.81 19.22 24.00 24.00 24.00
#> 135 144 75 121.1 172 74 28 148.1 143 176 102 176.1 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 116 21.1 64 191 65.1 67 162 186 152 12 160 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 193 147 44 200 95 62 152.1 83 20 146 53 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.1 191.1 141 163 104 34 44.1 54 141.1 176.2 12.1 200.1 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 165 193.1 196 102.1 173 46 83.1 82 165.1 17 142 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 47 98.1 104.1 151.1 12.2 163.1 103 148.2 135.1 152.2 11.1 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 109 191.2
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[44]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -1.851762e-05 8.159582e-01 5.744262e-01
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.668170698 0.004838492 0.646657593
#> grade_iii, Cure model
#> 1.224310784
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 158 20.14 1 74 1 0
#> 63 22.77 1 31 1 0
#> 125 15.65 1 67 1 0
#> 189 10.51 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 154 12.63 1 20 1 0
#> 42 12.43 1 49 0 1
#> 13 14.34 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 68 20.62 1 44 0 0
#> 99 21.19 1 38 0 1
#> 168 23.72 1 70 0 0
#> 159 10.55 1 50 0 1
#> 136 21.83 1 43 0 1
#> 5 16.43 1 51 0 1
#> 78 23.88 1 43 0 0
#> 40 18.00 1 28 1 0
#> 117 17.46 1 26 0 1
#> 194.1 22.40 1 38 0 1
#> 110 17.56 1 65 0 1
#> 124 9.73 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 51 18.23 1 83 0 1
#> 101 9.97 1 10 0 1
#> 125.1 15.65 1 67 1 0
#> 167.1 15.55 1 56 1 0
#> 90 20.94 1 50 0 1
#> 43 12.10 1 61 0 1
#> 180 14.82 1 37 0 0
#> 123 13.00 1 44 1 0
#> 167.2 15.55 1 56 1 0
#> 15 22.68 1 48 0 0
#> 59 10.16 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 136.1 21.83 1 43 0 1
#> 24 23.89 1 38 0 0
#> 79 16.23 1 54 1 0
#> 4 17.64 1 NA 0 1
#> 169 22.41 1 46 0 0
#> 189.1 10.51 1 NA 1 0
#> 13.1 14.34 1 54 0 1
#> 4.1 17.64 1 NA 0 1
#> 36 21.19 1 48 0 1
#> 128 20.35 1 35 0 1
#> 128.1 20.35 1 35 0 1
#> 100 16.07 1 60 0 0
#> 117.1 17.46 1 26 0 1
#> 56 12.21 1 60 0 0
#> 134 17.81 1 47 1 0
#> 159.1 10.55 1 50 0 1
#> 171 16.57 1 41 0 1
#> 180.1 14.82 1 37 0 0
#> 13.2 14.34 1 54 0 1
#> 128.2 20.35 1 35 0 1
#> 51.1 18.23 1 83 0 1
#> 170 19.54 1 43 0 1
#> 81 14.06 1 34 0 0
#> 8 18.43 1 32 0 0
#> 69 23.23 1 25 0 1
#> 90.1 20.94 1 50 0 1
#> 107.1 11.18 1 54 1 0
#> 89.1 11.44 1 NA 0 0
#> 107.2 11.18 1 54 1 0
#> 149 8.37 1 33 1 0
#> 55 19.34 1 69 0 1
#> 63.1 22.77 1 31 1 0
#> 86 23.81 1 58 0 1
#> 8.1 18.43 1 32 0 0
#> 129 23.41 1 53 1 0
#> 159.2 10.55 1 50 0 1
#> 149.1 8.37 1 33 1 0
#> 110.1 17.56 1 65 0 1
#> 149.2 8.37 1 33 1 0
#> 187 9.92 1 39 1 0
#> 39 15.59 1 37 0 1
#> 79.1 16.23 1 54 1 0
#> 70 7.38 1 30 1 0
#> 15.1 22.68 1 48 0 0
#> 90.2 20.94 1 50 0 1
#> 37 12.52 1 57 1 0
#> 68.1 20.62 1 44 0 0
#> 134.1 17.81 1 47 1 0
#> 13.3 14.34 1 54 0 1
#> 111 17.45 1 47 0 1
#> 192 16.44 1 31 1 0
#> 55.1 19.34 1 69 0 1
#> 77 7.27 1 67 0 1
#> 159.3 10.55 1 50 0 1
#> 56.1 12.21 1 60 0 0
#> 58 19.34 1 39 0 0
#> 43.1 12.10 1 61 0 1
#> 101.1 9.97 1 10 0 1
#> 70.1 7.38 1 30 1 0
#> 14 12.89 1 21 0 0
#> 57 14.46 1 45 0 1
#> 130 16.47 1 53 0 1
#> 13.4 14.34 1 54 0 1
#> 189.2 10.51 1 NA 1 0
#> 86.1 23.81 1 58 0 1
#> 197 21.60 1 69 1 0
#> 63.2 22.77 1 31 1 0
#> 169.1 22.41 1 46 0 0
#> 175 21.91 1 43 0 0
#> 166 19.98 1 48 0 0
#> 192.1 16.44 1 31 1 0
#> 181 16.46 1 45 0 1
#> 140 12.68 1 59 1 0
#> 24.1 23.89 1 38 0 0
#> 197.1 21.60 1 69 1 0
#> 88 18.37 1 47 0 0
#> 17 24.00 0 38 0 1
#> 98 24.00 0 34 1 0
#> 87 24.00 0 27 0 0
#> 118 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 3 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 148 24.00 0 61 1 0
#> 131 24.00 0 66 0 0
#> 31 24.00 0 36 0 1
#> 102 24.00 0 49 0 0
#> 27 24.00 0 63 1 0
#> 12 24.00 0 63 0 0
#> 141 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 47 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 148.1 24.00 0 61 1 0
#> 138 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 119 24.00 0 17 0 0
#> 122 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 80 24.00 0 41 0 0
#> 1 24.00 0 23 1 0
#> 21 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 53 24.00 0 32 0 1
#> 82.1 24.00 0 34 0 0
#> 74 24.00 0 43 0 1
#> 135 24.00 0 58 1 0
#> 196.1 24.00 0 19 0 0
#> 87.1 24.00 0 27 0 0
#> 156 24.00 0 50 1 0
#> 196.2 24.00 0 19 0 0
#> 200 24.00 0 64 0 0
#> 47.1 24.00 0 38 0 1
#> 160 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 147.1 24.00 0 76 1 0
#> 22 24.00 0 52 1 0
#> 74.1 24.00 0 43 0 1
#> 62 24.00 0 71 0 0
#> 33 24.00 0 53 0 0
#> 72 24.00 0 40 0 1
#> 138.1 24.00 0 44 1 0
#> 118.1 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 80.1 24.00 0 41 0 0
#> 65 24.00 0 57 1 0
#> 67 24.00 0 25 0 0
#> 191 24.00 0 60 0 1
#> 186 24.00 0 45 1 0
#> 31.1 24.00 0 36 0 1
#> 2 24.00 0 9 0 0
#> 146 24.00 0 63 1 0
#> 1.1 24.00 0 23 1 0
#> 119.1 24.00 0 17 0 0
#> 178 24.00 0 52 1 0
#> 138.2 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 71 24.00 0 51 0 0
#> 98.1 24.00 0 34 1 0
#> 126 24.00 0 48 0 0
#> 71.1 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 74.2 24.00 0 43 0 1
#> 53.1 24.00 0 32 0 1
#> 73 24.00 0 NA 0 1
#> 115.1 24.00 0 NA 1 0
#> 53.2 24.00 0 32 0 1
#> 31.2 24.00 0 36 0 1
#> 151 24.00 0 42 0 0
#> 132 24.00 0 55 0 0
#> 132.1 24.00 0 55 0 0
#> 143.1 24.00 0 51 0 0
#> 74.3 24.00 0 43 0 1
#> 83 24.00 0 6 0 0
#> 35.1 24.00 0 51 0 0
#> 132.2 24.00 0 55 0 0
#> 28 24.00 0 67 1 0
#> 94.1 24.00 0 51 0 1
#> 198.1 24.00 0 66 0 1
#> 182 24.00 0 35 0 0
#> 120 24.00 0 68 0 1
#> 12.1 24.00 0 63 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.668 NA NA NA
#> 2 age, Cure model 0.00484 NA NA NA
#> 3 grade_ii, Cure model 0.647 NA NA NA
#> 4 grade_iii, Cure model 1.22 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0000185 NA NA NA
#> 2 grade_ii, Survival model 0.816 NA NA NA
#> 3 grade_iii, Survival model 0.574 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.668171 0.004838 0.646658 1.224311
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 245.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.668170698 0.004838492 0.646657593 1.224310784
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -1.851762e-05 8.159582e-01 5.744262e-01
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.31580573 0.50017801 0.22229806 0.74249346 0.55514831 0.86292848
#> [7] 0.87564743 0.80452358 0.45155855 0.40035849 0.16127642 0.92498396
#> [13] 0.35407129 0.71313574 0.08511651 0.60882966 0.65053472 0.31580573
#> [19] 0.63419400 0.76377104 0.59125757 0.94854560 0.74249346 0.76377104
#> [25] 0.42169430 0.89448753 0.78411060 0.84345826 0.76377104 0.26175859
#> [31] 0.90689795 0.35407129 0.03129058 0.72063759 0.28878016 0.80452358
#> [37] 0.40035849 0.47169510 0.47169510 0.73518389 0.65053472 0.88194237
#> [43] 0.61752083 0.92498396 0.67455157 0.78411060 0.80452358 0.47169510
#> [49] 0.59125757 0.51907882 0.83688371 0.56421242 0.20390583 0.42169430
#> [55] 0.90689795 0.90689795 0.96613011 0.52839788 0.22229806 0.11881876
#> [61] 0.56421242 0.18413321 0.92498396 0.96613011 0.63419400 0.96613011
#> [67] 0.96028667 0.75669058 0.72063759 0.98316751 0.26175859 0.42169430
#> [73] 0.86931724 0.45155855 0.61752083 0.80452358 0.66656334 0.69808903
#> [79] 0.52839788 0.99439492 0.92498396 0.88194237 0.52839788 0.89448753
#> [85] 0.94854560 0.98316751 0.84996889 0.79772979 0.68246719 0.80452358
#> [91] 0.11881876 0.37810444 0.22229806 0.28878016 0.34115275 0.50962834
#> [97] 0.69808903 0.69031234 0.85647955 0.03129058 0.37810444 0.58219542
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 194 158 63 125 179 154 42 13 68 99 168 159 136
#> 22.40 20.14 22.77 15.65 18.63 12.63 12.43 14.34 20.62 21.19 23.72 10.55 21.83
#> 5 78 40 117 194.1 110 167 51 101 125.1 167.1 90 43
#> 16.43 23.88 18.00 17.46 22.40 17.56 15.55 18.23 9.97 15.65 15.55 20.94 12.10
#> 180 123 167.2 15 107 136.1 24 79 169 13.1 36 128 128.1
#> 14.82 13.00 15.55 22.68 11.18 21.83 23.89 16.23 22.41 14.34 21.19 20.35 20.35
#> 100 117.1 56 134 159.1 171 180.1 13.2 128.2 51.1 170 81 8
#> 16.07 17.46 12.21 17.81 10.55 16.57 14.82 14.34 20.35 18.23 19.54 14.06 18.43
#> 69 90.1 107.1 107.2 149 55 63.1 86 8.1 129 159.2 149.1 110.1
#> 23.23 20.94 11.18 11.18 8.37 19.34 22.77 23.81 18.43 23.41 10.55 8.37 17.56
#> 149.2 187 39 79.1 70 15.1 90.2 37 68.1 134.1 13.3 111 192
#> 8.37 9.92 15.59 16.23 7.38 22.68 20.94 12.52 20.62 17.81 14.34 17.45 16.44
#> 55.1 77 159.3 56.1 58 43.1 101.1 70.1 14 57 130 13.4 86.1
#> 19.34 7.27 10.55 12.21 19.34 12.10 9.97 7.38 12.89 14.46 16.47 14.34 23.81
#> 197 63.2 169.1 175 166 192.1 181 140 24.1 197.1 88 17 98
#> 21.60 22.77 22.41 21.91 19.98 16.44 16.46 12.68 23.89 21.60 18.37 24.00 24.00
#> 87 118 35 172 3 196 148 131 31 102 27 12 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 47 82 148.1 138 165 94 119 122 147 80 1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 82.1 74 135 196.1 87.1 156 196.2 200 47.1 160 19 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 74.1 62 33 72 138.1 118.1 198 80.1 65 67 191 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 2 146 1.1 119.1 178 138.2 7 71 98.1 126 71.1 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.2 53.1 53.2 31.2 151 132 132.1 143.1 74.3 83 35.1 132.2 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 198.1 182 120 12.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[45]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009930836 0.706950771 0.893549782
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.73985326 0.02590672 -0.83394217
#> grade_iii, Cure model
#> -0.30470206
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 52 10.42 1 52 0 1
#> 195 11.76 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 88 18.37 1 47 0 0
#> 99 21.19 1 38 0 1
#> 40 18.00 1 28 1 0
#> 117 17.46 1 26 0 1
#> 25 6.32 1 34 1 0
#> 197 21.60 1 69 1 0
#> 30 17.43 1 78 0 0
#> 8 18.43 1 32 0 0
#> 50 10.02 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 113 22.86 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 199 19.81 1 NA 0 1
#> 8.1 18.43 1 32 0 0
#> 57 14.46 1 45 0 1
#> 14 12.89 1 21 0 0
#> 97 19.14 1 65 0 1
#> 184 17.77 1 38 0 0
#> 18 15.21 1 49 1 0
#> 197.1 21.60 1 69 1 0
#> 50.1 10.02 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 70 7.38 1 30 1 0
#> 169 22.41 1 46 0 0
#> 129 23.41 1 53 1 0
#> 59 10.16 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 184.1 17.77 1 38 0 0
#> 77 7.27 1 67 0 1
#> 43 12.10 1 61 0 1
#> 166.1 19.98 1 48 0 0
#> 13 14.34 1 54 0 1
#> 14.1 12.89 1 21 0 0
#> 90 20.94 1 50 0 1
#> 37 12.52 1 57 1 0
#> 58 19.34 1 39 0 0
#> 30.1 17.43 1 78 0 0
#> 79 16.23 1 54 1 0
#> 51 18.23 1 83 0 1
#> 114.1 13.68 1 NA 0 0
#> 139 21.49 1 63 1 0
#> 15 22.68 1 48 0 0
#> 66 22.13 1 53 0 0
#> 124 9.73 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 43.1 12.10 1 61 0 1
#> 24 23.89 1 38 0 0
#> 40.1 18.00 1 28 1 0
#> 41 18.02 1 40 1 0
#> 40.2 18.00 1 28 1 0
#> 5 16.43 1 51 0 1
#> 39 15.59 1 37 0 1
#> 45 17.42 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 100 16.07 1 60 0 0
#> 8.2 18.43 1 32 0 0
#> 189 10.51 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 88.1 18.37 1 47 0 0
#> 164 23.60 1 76 0 1
#> 13.1 14.34 1 54 0 1
#> 24.1 23.89 1 38 0 0
#> 150 20.33 1 48 0 0
#> 127.1 3.53 1 62 0 1
#> 6 15.64 1 39 0 0
#> 149 8.37 1 33 1 0
#> 49 12.19 1 48 1 0
#> 155 13.08 1 26 0 0
#> 76.1 19.22 1 54 0 1
#> 89.1 11.44 1 NA 0 0
#> 15.1 22.68 1 48 0 0
#> 81 14.06 1 34 0 0
#> 117.1 17.46 1 26 0 1
#> 24.2 23.89 1 38 0 0
#> 49.1 12.19 1 48 1 0
#> 16 8.71 1 71 0 1
#> 157.1 15.10 1 47 0 0
#> 108 18.29 1 39 0 1
#> 170 19.54 1 43 0 1
#> 93 10.33 1 52 0 1
#> 16.1 8.71 1 71 0 1
#> 91 5.33 1 61 0 1
#> 166.2 19.98 1 48 0 0
#> 30.2 17.43 1 78 0 0
#> 45.1 17.42 1 54 0 1
#> 155.1 13.08 1 26 0 0
#> 179.1 18.63 1 42 0 0
#> 51.1 18.23 1 83 0 1
#> 179.2 18.63 1 42 0 0
#> 30.3 17.43 1 78 0 0
#> 166.3 19.98 1 48 0 0
#> 18.1 15.21 1 49 1 0
#> 6.1 15.64 1 39 0 0
#> 105 19.75 1 60 0 0
#> 93.1 10.33 1 52 0 1
#> 134 17.81 1 47 1 0
#> 113.1 22.86 1 34 0 0
#> 158 20.14 1 74 1 0
#> 179.3 18.63 1 42 0 0
#> 97.1 19.14 1 65 0 1
#> 76.2 19.22 1 54 0 1
#> 43.2 12.10 1 61 0 1
#> 107 11.18 1 54 1 0
#> 168 23.72 1 70 0 0
#> 188 16.16 1 46 0 1
#> 140 12.68 1 59 1 0
#> 97.2 19.14 1 65 0 1
#> 51.2 18.23 1 83 0 1
#> 11 24.00 0 42 0 1
#> 185 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#> 112 24.00 0 61 0 0
#> 74 24.00 0 43 0 1
#> 120 24.00 0 68 0 1
#> 2 24.00 0 9 0 0
#> 143 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 27 24.00 0 63 1 0
#> 87 24.00 0 27 0 0
#> 38 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 176 24.00 0 43 0 1
#> 83 24.00 0 6 0 0
#> 1 24.00 0 23 1 0
#> 2.1 24.00 0 9 0 0
#> 102 24.00 0 49 0 0
#> 94 24.00 0 51 0 1
#> 198 24.00 0 66 0 1
#> 72 24.00 0 40 0 1
#> 1.1 24.00 0 23 1 0
#> 44.1 24.00 0 56 0 0
#> 196 24.00 0 19 0 0
#> 196.1 24.00 0 19 0 0
#> 34 24.00 0 36 0 0
#> 94.1 24.00 0 51 0 1
#> 160 24.00 0 31 1 0
#> 176.1 24.00 0 43 0 1
#> 191 24.00 0 60 0 1
#> 3 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 3.1 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 12 24.00 0 63 0 0
#> 115 24.00 0 NA 1 0
#> 80 24.00 0 41 0 0
#> 31.1 24.00 0 36 0 1
#> 71 24.00 0 51 0 0
#> 160.1 24.00 0 31 1 0
#> 31.2 24.00 0 36 0 1
#> 84 24.00 0 39 0 1
#> 53 24.00 0 32 0 1
#> 98 24.00 0 34 1 0
#> 65 24.00 0 57 1 0
#> 1.2 24.00 0 23 1 0
#> 178.1 24.00 0 52 1 0
#> 22 24.00 0 52 1 0
#> 131 24.00 0 66 0 0
#> 2.2 24.00 0 9 0 0
#> 11.1 24.00 0 42 0 1
#> 94.2 24.00 0 51 0 1
#> 12.1 24.00 0 63 0 0
#> 120.1 24.00 0 68 0 1
#> 147 24.00 0 76 1 0
#> 148 24.00 0 61 1 0
#> 126 24.00 0 48 0 0
#> 28 24.00 0 67 1 0
#> 146 24.00 0 63 1 0
#> 98.1 24.00 0 34 1 0
#> 83.1 24.00 0 6 0 0
#> 47 24.00 0 38 0 1
#> 138 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 185.1 24.00 0 44 1 0
#> 22.1 24.00 0 52 1 0
#> 27.1 24.00 0 63 1 0
#> 47.1 24.00 0 38 0 1
#> 44.2 24.00 0 56 0 0
#> 82 24.00 0 34 0 0
#> 122 24.00 0 66 0 0
#> 65.1 24.00 0 57 1 0
#> 176.2 24.00 0 43 0 1
#> 102.1 24.00 0 49 0 0
#> 118.1 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 173.1 24.00 0 19 0 1
#> 67 24.00 0 25 0 0
#> 173.2 24.00 0 19 0 1
#> 71.1 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 122.1 24.00 0 66 0 0
#> 1.3 24.00 0 23 1 0
#> 193 24.00 0 45 0 1
#> 95 24.00 0 68 0 1
#> 191.1 24.00 0 60 0 1
#> 95.1 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.740 NA NA NA
#> 2 age, Cure model 0.0259 NA NA NA
#> 3 grade_ii, Cure model -0.834 NA NA NA
#> 4 grade_iii, Cure model -0.305 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00993 NA NA NA
#> 2 grade_ii, Survival model 0.707 NA NA NA
#> 3 grade_iii, Survival model 0.894 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.73985 0.02591 -0.83394 -0.30470
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 246.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.73985326 0.02590672 -0.83394217 -0.30470206
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009930836 0.706950771 0.893549782
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.885424186 0.981297869 0.386537224 0.137030452 0.461978994 0.523351832
#> [7] 0.962359048 0.104776260 0.543303249 0.354733592 0.695770835 0.046345775
#> [13] 0.354733592 0.716020778 0.776081113 0.284194011 0.502701796 0.675738366
#> [19] 0.104776260 0.178328776 0.943281097 0.082785346 0.037794611 0.816462484
#> [25] 0.502701796 0.952832311 0.846343981 0.178328776 0.726137242 0.776081113
#> [31] 0.147486133 0.806357543 0.242259050 0.543303249 0.614714981 0.419432834
#> [37] 0.126007243 0.063567318 0.093515982 0.253531133 0.846343981 0.004538362
#> [43] 0.461978994 0.451218661 0.461978994 0.604492372 0.665571950 0.584058095
#> [49] 0.635006919 0.354733592 0.313956766 0.386537224 0.028854105 0.726137242
#> [55] 0.004538362 0.157593045 0.981297869 0.645180432 0.933680761 0.826505007
#> [61] 0.756026865 0.253531133 0.063567318 0.745993336 0.523351832 0.004538362
#> [67] 0.826505007 0.914488268 0.695770835 0.408497425 0.231152966 0.895211892
#> [73] 0.914488268 0.971843841 0.178328776 0.543303249 0.584058095 0.756026865
#> [79] 0.313956766 0.419432834 0.313956766 0.543303249 0.178328776 0.675738366
#> [85] 0.645180432 0.219720536 0.895211892 0.492402942 0.046345775 0.167951997
#> [91] 0.313956766 0.284194011 0.253531133 0.846343981 0.875586663 0.019511669
#> [97] 0.624906053 0.796233407 0.284194011 0.419432834 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 52 127 88 99 40 117 25 197 30 8 157 113 8.1
#> 10.42 3.53 18.37 21.19 18.00 17.46 6.32 21.60 17.43 18.43 15.10 22.86 18.43
#> 57 14 97 184 18 197.1 166 70 169 129 42 184.1 77
#> 14.46 12.89 19.14 17.77 15.21 21.60 19.98 7.38 22.41 23.41 12.43 17.77 7.27
#> 43 166.1 13 14.1 90 37 58 30.1 79 51 139 15 66
#> 12.10 19.98 14.34 12.89 20.94 12.52 19.34 17.43 16.23 18.23 21.49 22.68 22.13
#> 76 43.1 24 40.1 41 40.2 5 39 45 100 8.2 179 88.1
#> 19.22 12.10 23.89 18.00 18.02 18.00 16.43 15.59 17.42 16.07 18.43 18.63 18.37
#> 164 13.1 24.1 150 127.1 6 149 49 155 76.1 15.1 81 117.1
#> 23.60 14.34 23.89 20.33 3.53 15.64 8.37 12.19 13.08 19.22 22.68 14.06 17.46
#> 24.2 49.1 16 157.1 108 170 93 16.1 91 166.2 30.2 45.1 155.1
#> 23.89 12.19 8.71 15.10 18.29 19.54 10.33 8.71 5.33 19.98 17.43 17.42 13.08
#> 179.1 51.1 179.2 30.3 166.3 18.1 6.1 105 93.1 134 113.1 158 179.3
#> 18.63 18.23 18.63 17.43 19.98 15.21 15.64 19.75 10.33 17.81 22.86 20.14 18.63
#> 97.1 76.2 43.2 107 168 188 140 97.2 51.2 11 185 178 112
#> 19.14 19.22 12.10 11.18 23.72 16.16 12.68 19.14 18.23 24.00 24.00 24.00 24.00
#> 74 120 2 143 44 27 87 38 135 176 83 1 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 94 198 72 1.1 44.1 196 196.1 34 94.1 160 176.1 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 118 31 3.1 104 12 80 31.1 71 160.1 31.2 84 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 65 1.2 178.1 22 131 2.2 11.1 94.2 12.1 120.1 147 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 28 146 98.1 83.1 47 138 173 185.1 22.1 27.1 47.1 44.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 122 65.1 176.2 102.1 118.1 109 173.1 67 173.2 71.1 132 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.3 193 95 191.1 95.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[46]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01297936 0.51170329 0.09745754
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.82327084 0.01972796 -0.17432335
#> grade_iii, Cure model
#> 0.50093867
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 92 22.92 1 47 0 1
#> 13 14.34 1 54 0 1
#> 32 20.90 1 37 1 0
#> 170 19.54 1 43 0 1
#> 105 19.75 1 60 0 0
#> 61 10.12 1 36 0 1
#> 157 15.10 1 47 0 0
#> 169 22.41 1 46 0 0
#> 150 20.33 1 48 0 0
#> 4 17.64 1 NA 0 1
#> 168 23.72 1 70 0 0
#> 42 12.43 1 49 0 1
#> 16 8.71 1 71 0 1
#> 57 14.46 1 45 0 1
#> 110 17.56 1 65 0 1
#> 125 15.65 1 67 1 0
#> 23 16.92 1 61 0 0
#> 153 21.33 1 55 1 0
#> 157.1 15.10 1 47 0 0
#> 10 10.53 1 34 0 0
#> 154 12.63 1 20 1 0
#> 164 23.60 1 76 0 1
#> 169.1 22.41 1 46 0 0
#> 101 9.97 1 10 0 1
#> 153.1 21.33 1 55 1 0
#> 61.1 10.12 1 36 0 1
#> 77 7.27 1 67 0 1
#> 61.2 10.12 1 36 0 1
#> 42.1 12.43 1 49 0 1
#> 175 21.91 1 43 0 0
#> 77.1 7.27 1 67 0 1
#> 199 19.81 1 NA 0 1
#> 42.2 12.43 1 49 0 1
#> 30 17.43 1 78 0 0
#> 70 7.38 1 30 1 0
#> 154.1 12.63 1 20 1 0
#> 183 9.24 1 67 1 0
#> 36 21.19 1 48 0 1
#> 113 22.86 1 34 0 0
#> 108 18.29 1 39 0 1
#> 5 16.43 1 51 0 1
#> 29 15.45 1 68 1 0
#> 49 12.19 1 48 1 0
#> 81 14.06 1 34 0 0
#> 179 18.63 1 42 0 0
#> 129 23.41 1 53 1 0
#> 145 10.07 1 65 1 0
#> 149 8.37 1 33 1 0
#> 139 21.49 1 63 1 0
#> 107 11.18 1 54 1 0
#> 18 15.21 1 49 1 0
#> 91 5.33 1 61 0 1
#> 61.3 10.12 1 36 0 1
#> 88 18.37 1 47 0 0
#> 76 19.22 1 54 0 1
#> 149.1 8.37 1 33 1 0
#> 169.2 22.41 1 46 0 0
#> 177 12.53 1 75 0 0
#> 192 16.44 1 31 1 0
#> 39 15.59 1 37 0 1
#> 66 22.13 1 53 0 0
#> 10.1 10.53 1 34 0 0
#> 134 17.81 1 47 1 0
#> 145.1 10.07 1 65 1 0
#> 10.2 10.53 1 34 0 0
#> 192.1 16.44 1 31 1 0
#> 14 12.89 1 21 0 0
#> 96 14.54 1 33 0 1
#> 117 17.46 1 26 0 1
#> 86 23.81 1 58 0 1
#> 199.1 19.81 1 NA 0 1
#> 13.1 14.34 1 54 0 1
#> 153.2 21.33 1 55 1 0
#> 86.1 23.81 1 58 0 1
#> 40 18.00 1 28 1 0
#> 36.1 21.19 1 48 0 1
#> 30.1 17.43 1 78 0 0
#> 58 19.34 1 39 0 0
#> 93 10.33 1 52 0 1
#> 79 16.23 1 54 1 0
#> 107.1 11.18 1 54 1 0
#> 100 16.07 1 60 0 0
#> 133 14.65 1 57 0 0
#> 194 22.40 1 38 0 1
#> 70.1 7.38 1 30 1 0
#> 70.2 7.38 1 30 1 0
#> 170.1 19.54 1 43 0 1
#> 124 9.73 1 NA 1 0
#> 86.2 23.81 1 58 0 1
#> 91.1 5.33 1 61 0 1
#> 127 3.53 1 62 0 1
#> 183.1 9.24 1 67 1 0
#> 100.1 16.07 1 60 0 0
#> 86.3 23.81 1 58 0 1
#> 183.2 9.24 1 67 1 0
#> 125.1 15.65 1 67 1 0
#> 16.1 8.71 1 71 0 1
#> 96.1 14.54 1 33 0 1
#> 10.3 10.53 1 34 0 0
#> 157.2 15.10 1 47 0 0
#> 30.2 17.43 1 78 0 0
#> 169.3 22.41 1 46 0 0
#> 183.3 9.24 1 67 1 0
#> 159 10.55 1 50 0 1
#> 66.1 22.13 1 53 0 0
#> 97 19.14 1 65 0 1
#> 51 18.23 1 83 0 1
#> 51.1 18.23 1 83 0 1
#> 10.4 10.53 1 34 0 0
#> 155 13.08 1 26 0 0
#> 97.1 19.14 1 65 0 1
#> 108.1 18.29 1 39 0 1
#> 173 24.00 0 19 0 1
#> 121 24.00 0 57 1 0
#> 152 24.00 0 36 0 1
#> 65 24.00 0 57 1 0
#> 83 24.00 0 6 0 0
#> 1 24.00 0 23 1 0
#> 126 24.00 0 48 0 0
#> 186 24.00 0 45 1 0
#> 54 24.00 0 53 1 0
#> 137 24.00 0 45 1 0
#> 84 24.00 0 39 0 1
#> 84.1 24.00 0 39 0 1
#> 98 24.00 0 34 1 0
#> 193 24.00 0 45 0 1
#> 120 24.00 0 68 0 1
#> 74 24.00 0 43 0 1
#> 48 24.00 0 31 1 0
#> 173.1 24.00 0 19 0 1
#> 186.1 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 94 24.00 0 51 0 1
#> 71 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 48.1 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 122 24.00 0 66 0 0
#> 151 24.00 0 42 0 0
#> 163 24.00 0 66 0 0
#> 84.2 24.00 0 39 0 1
#> 144 24.00 0 28 0 1
#> 20.1 24.00 0 46 1 0
#> 122.1 24.00 0 66 0 0
#> 122.2 24.00 0 66 0 0
#> 74.1 24.00 0 43 0 1
#> 31 24.00 0 36 0 1
#> 147 24.00 0 76 1 0
#> 19 24.00 0 57 0 1
#> 67 24.00 0 25 0 0
#> 44 24.00 0 56 0 0
#> 62 24.00 0 71 0 0
#> 193.1 24.00 0 45 0 1
#> 83.1 24.00 0 6 0 0
#> 28 24.00 0 67 1 0
#> 121.1 24.00 0 57 1 0
#> 151.1 24.00 0 42 0 0
#> 65.1 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 1.1 24.00 0 23 1 0
#> 173.2 24.00 0 19 0 1
#> 33 24.00 0 53 0 0
#> 165 24.00 0 47 0 0
#> 98.1 24.00 0 34 1 0
#> 152.1 24.00 0 36 0 1
#> 53 24.00 0 32 0 1
#> 191 24.00 0 60 0 1
#> 62.1 24.00 0 71 0 0
#> 54.1 24.00 0 53 1 0
#> 172 24.00 0 41 0 0
#> 165.1 24.00 0 47 0 0
#> 73 24.00 0 NA 0 1
#> 200 24.00 0 64 0 0
#> 147.1 24.00 0 76 1 0
#> 131 24.00 0 66 0 0
#> 20.2 24.00 0 46 1 0
#> 119 24.00 0 17 0 0
#> 198 24.00 0 66 0 1
#> 138 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 74.2 24.00 0 43 0 1
#> 3 24.00 0 31 1 0
#> 48.2 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 118 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 174 24.00 0 49 1 0
#> 9 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 67.1 24.00 0 25 0 0
#> 147.2 24.00 0 76 1 0
#> 73.1 24.00 0 NA 0 1
#> 131.1 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 138.1 24.00 0 44 1 0
#> 71.1 24.00 0 51 0 0
#> 1.2 24.00 0 23 1 0
#> 156 24.00 0 50 1 0
#> 48.3 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.823 NA NA NA
#> 2 age, Cure model 0.0197 NA NA NA
#> 3 grade_ii, Cure model -0.174 NA NA NA
#> 4 grade_iii, Cure model 0.501 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0130 NA NA NA
#> 2 grade_ii, Survival model 0.512 NA NA NA
#> 3 grade_iii, Survival model 0.0975 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.82327 0.01973 -0.17432 0.50094
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.4
#> Residual Deviance: 258.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.82327084 0.01972796 -0.17432335 0.50093867
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01297936 0.51170329 0.09745754
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0125042032 0.4481308551 0.0861935172 0.1048304748 0.0984096155
#> [6] 0.6965115685 0.3727952150 0.0192636051 0.0922077454 0.0045216274
#> [11] 0.5399260246 0.8380085260 0.4369592541 0.2106312090 0.3218655402
#> [16] 0.2549483138 0.0587756379 0.3727952150 0.6232148706 0.5054909103
#> [21] 0.0067670980 0.0192636051 0.7728907610 0.0587756379 0.6965115685
#> [26] 0.9314880931 0.6965115685 0.5399260246 0.0479040371 0.9314880931
#> [31] 0.5399260246 0.2279495636 0.8917626639 0.5054909103 0.7859691276
#> [36] 0.0745600269 0.0157538470 0.1615693257 0.2830387084 0.3520930911
#> [41] 0.5751070643 0.4706991288 0.1462150073 0.0095634203 0.7469691792
#> [46] 0.8649218723 0.0532665583 0.5871080059 0.3624268687 0.9585810492
#> [51] 0.6965115685 0.1538046579 0.1247064196 0.8649218723 0.0192636051
#> [56] 0.5282586206 0.2644765856 0.3418524659 0.0382162905 0.6232148706
#> [61] 0.2021902590 0.7469691792 0.6232148706 0.2644765856 0.4938235744
#> [66] 0.4151140960 0.2192538837 0.0006590632 0.4481308551 0.0587756379
#> [71] 0.0006590632 0.1937822267 0.0745600269 0.2279495636 0.1178508473
#> [76] 0.6838316551 0.2926149028 0.5871080059 0.3022454451 0.4042078919
#> [81] 0.0336435156 0.8917626639 0.8917626639 0.1048304748 0.0006590632
#> [86] 0.9585810492 0.9860628399 0.7859691276 0.3022454451 0.0006590632
#> [91] 0.7859691276 0.3218655402 0.8380085260 0.4151140960 0.6232148706
#> [96] 0.3727952150 0.2279495636 0.0192636051 0.7859691276 0.6110315456
#> [101] 0.0382162905 0.1317371594 0.1772187837 0.1772187837 0.6232148706
#> [106] 0.4822216453 0.1317371594 0.1615693257 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 92 13 32 170 105 61 157 169 150 168 42 16 57
#> 22.92 14.34 20.90 19.54 19.75 10.12 15.10 22.41 20.33 23.72 12.43 8.71 14.46
#> 110 125 23 153 157.1 10 154 164 169.1 101 153.1 61.1 77
#> 17.56 15.65 16.92 21.33 15.10 10.53 12.63 23.60 22.41 9.97 21.33 10.12 7.27
#> 61.2 42.1 175 77.1 42.2 30 70 154.1 183 36 113 108 5
#> 10.12 12.43 21.91 7.27 12.43 17.43 7.38 12.63 9.24 21.19 22.86 18.29 16.43
#> 29 49 81 179 129 145 149 139 107 18 91 61.3 88
#> 15.45 12.19 14.06 18.63 23.41 10.07 8.37 21.49 11.18 15.21 5.33 10.12 18.37
#> 76 149.1 169.2 177 192 39 66 10.1 134 145.1 10.2 192.1 14
#> 19.22 8.37 22.41 12.53 16.44 15.59 22.13 10.53 17.81 10.07 10.53 16.44 12.89
#> 96 117 86 13.1 153.2 86.1 40 36.1 30.1 58 93 79 107.1
#> 14.54 17.46 23.81 14.34 21.33 23.81 18.00 21.19 17.43 19.34 10.33 16.23 11.18
#> 100 133 194 70.1 70.2 170.1 86.2 91.1 127 183.1 100.1 86.3 183.2
#> 16.07 14.65 22.40 7.38 7.38 19.54 23.81 5.33 3.53 9.24 16.07 23.81 9.24
#> 125.1 16.1 96.1 10.3 157.2 30.2 169.3 183.3 159 66.1 97 51 51.1
#> 15.65 8.71 14.54 10.53 15.10 17.43 22.41 9.24 10.55 22.13 19.14 18.23 18.23
#> 10.4 155 97.1 108.1 173 121 152 65 83 1 126 186 54
#> 10.53 13.08 19.14 18.29 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 84 84.1 98 193 120 74 48 173.1 186.1 27 94 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 48.1 20 122 151 163 84.2 144 20.1 122.1 122.2 74.1 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 19 67 44 62 193.1 83.1 28 121.1 151.1 65.1 35 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.2 33 165 98.1 152.1 53 191 62.1 54.1 172 165.1 200 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 20.2 119 198 138 143 74.2 3 48.2 47 118 142 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 17 82 67.1 147.2 131.1 80 138.1 71.1 1.2 156 48.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[47]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01264571 0.11827246 0.07843804
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.83727352 -0.02394213 0.26240742
#> grade_iii, Cure model
#> 1.18859904
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 18 15.21 1 49 1 0
#> 41 18.02 1 40 1 0
#> 187 9.92 1 39 1 0
#> 136 21.83 1 43 0 1
#> 57 14.46 1 45 0 1
#> 153 21.33 1 55 1 0
#> 50 10.02 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 145 10.07 1 65 1 0
#> 77 7.27 1 67 0 1
#> 89 11.44 1 NA 0 0
#> 107 11.18 1 54 1 0
#> 63 22.77 1 31 1 0
#> 155 13.08 1 26 0 0
#> 159 10.55 1 50 0 1
#> 117 17.46 1 26 0 1
#> 85 16.44 1 36 0 0
#> 99 21.19 1 38 0 1
#> 136.1 21.83 1 43 0 1
#> 170 19.54 1 43 0 1
#> 89.1 11.44 1 NA 0 0
#> 149 8.37 1 33 1 0
#> 61 10.12 1 36 0 1
#> 25 6.32 1 34 1 0
#> 180 14.82 1 37 0 0
#> 8 18.43 1 32 0 0
#> 5 16.43 1 51 0 1
#> 124 9.73 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 166 19.98 1 48 0 0
#> 107.1 11.18 1 54 1 0
#> 114 13.68 1 NA 0 0
#> 36 21.19 1 48 0 1
#> 32 20.90 1 37 1 0
#> 100 16.07 1 60 0 0
#> 136.2 21.83 1 43 0 1
#> 154 12.63 1 20 1 0
#> 16 8.71 1 71 0 1
#> 25.1 6.32 1 34 1 0
#> 180.1 14.82 1 37 0 0
#> 153.1 21.33 1 55 1 0
#> 18.1 15.21 1 49 1 0
#> 26 15.77 1 49 0 1
#> 50.1 10.02 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 154.1 12.63 1 20 1 0
#> 15 22.68 1 48 0 0
#> 6.1 15.64 1 39 0 0
#> 154.2 12.63 1 20 1 0
#> 92 22.92 1 47 0 1
#> 18.2 15.21 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 59 10.16 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 92.1 22.92 1 47 0 1
#> 128 20.35 1 35 0 1
#> 32.1 20.90 1 37 1 0
#> 96 14.54 1 33 0 1
#> 105 19.75 1 60 0 0
#> 36.1 21.19 1 48 0 1
#> 189.1 10.51 1 NA 1 0
#> 192.1 16.44 1 31 1 0
#> 14 12.89 1 21 0 0
#> 117.1 17.46 1 26 0 1
#> 159.1 10.55 1 50 0 1
#> 168 23.72 1 70 0 0
#> 166.1 19.98 1 48 0 0
#> 195 11.76 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 23 16.92 1 61 0 0
#> 59.1 10.16 1 NA 1 0
#> 63.1 22.77 1 31 1 0
#> 175 21.91 1 43 0 0
#> 129 23.41 1 53 1 0
#> 168.1 23.72 1 70 0 0
#> 130.1 16.47 1 53 0 1
#> 56 12.21 1 60 0 0
#> 129.1 23.41 1 53 1 0
#> 63.2 22.77 1 31 1 0
#> 51 18.23 1 83 0 1
#> 157 15.10 1 47 0 0
#> 58 19.34 1 39 0 0
#> 101 9.97 1 10 0 1
#> 32.2 20.90 1 37 1 0
#> 70 7.38 1 30 1 0
#> 194 22.40 1 38 0 1
#> 51.1 18.23 1 83 0 1
#> 78 23.88 1 43 0 0
#> 43 12.10 1 61 0 1
#> 81 14.06 1 34 0 0
#> 145.1 10.07 1 65 1 0
#> 18.3 15.21 1 49 1 0
#> 114.1 13.68 1 NA 0 0
#> 29 15.45 1 68 1 0
#> 36.2 21.19 1 48 0 1
#> 133 14.65 1 57 0 0
#> 110 17.56 1 65 0 1
#> 50.2 10.02 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 63.3 22.77 1 31 1 0
#> 59.2 10.16 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 192.2 16.44 1 31 1 0
#> 155.1 13.08 1 26 0 0
#> 192.3 16.44 1 31 1 0
#> 158 20.14 1 74 1 0
#> 90 20.94 1 50 0 1
#> 14.1 12.89 1 21 0 0
#> 60.1 13.15 1 38 1 0
#> 10 10.53 1 34 0 0
#> 49 12.19 1 48 1 0
#> 65 24.00 0 57 1 0
#> 115 24.00 0 NA 1 0
#> 17 24.00 0 38 0 1
#> 146 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 156 24.00 0 50 1 0
#> 200 24.00 0 64 0 0
#> 163 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 11 24.00 0 42 0 1
#> 28 24.00 0 67 1 0
#> 152 24.00 0 36 0 1
#> 27.1 24.00 0 63 1 0
#> 7 24.00 0 37 1 0
#> 173 24.00 0 19 0 1
#> 9 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 35 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 67 24.00 0 25 0 0
#> 104 24.00 0 50 1 0
#> 193 24.00 0 45 0 1
#> 67.1 24.00 0 25 0 0
#> 193.1 24.00 0 45 0 1
#> 151 24.00 0 42 0 0
#> 35.1 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 137 24.00 0 45 1 0
#> 28.1 24.00 0 67 1 0
#> 191 24.00 0 60 0 1
#> 186 24.00 0 45 1 0
#> 98 24.00 0 34 1 0
#> 3 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 22 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 138 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 142 24.00 0 53 0 0
#> 31 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 137.1 24.00 0 45 1 0
#> 138.1 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 54.1 24.00 0 53 1 0
#> 44 24.00 0 56 0 0
#> 186.1 24.00 0 45 1 0
#> 120 24.00 0 68 0 1
#> 62.1 24.00 0 71 0 0
#> 137.2 24.00 0 45 1 0
#> 176 24.00 0 43 0 1
#> 182.1 24.00 0 35 0 0
#> 115.1 24.00 0 NA 1 0
#> 200.1 24.00 0 64 0 0
#> 135.1 24.00 0 58 1 0
#> 62.2 24.00 0 71 0 0
#> 142.1 24.00 0 53 0 0
#> 143 24.00 0 51 0 0
#> 200.2 24.00 0 64 0 0
#> 120.1 24.00 0 68 0 1
#> 102 24.00 0 49 0 0
#> 115.2 24.00 0 NA 1 0
#> 28.2 24.00 0 67 1 0
#> 65.1 24.00 0 57 1 0
#> 131 24.00 0 66 0 0
#> 64 24.00 0 43 0 0
#> 160 24.00 0 31 1 0
#> 137.3 24.00 0 45 1 0
#> 102.1 24.00 0 49 0 0
#> 27.2 24.00 0 63 1 0
#> 165.1 24.00 0 47 0 0
#> 33 24.00 0 53 0 0
#> 67.2 24.00 0 25 0 0
#> 182.2 24.00 0 35 0 0
#> 82 24.00 0 34 0 0
#> 163.1 24.00 0 66 0 0
#> 119 24.00 0 17 0 0
#> 132 24.00 0 55 0 0
#> 11.1 24.00 0 42 0 1
#> 84 24.00 0 39 0 1
#> 174 24.00 0 49 1 0
#> 31.1 24.00 0 36 0 1
#> 22.1 24.00 0 52 1 0
#> 148 24.00 0 61 1 0
#> 137.4 24.00 0 45 1 0
#> 161 24.00 0 45 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.837 NA NA NA
#> 2 age, Cure model -0.0239 NA NA NA
#> 3 grade_ii, Cure model 0.262 NA NA NA
#> 4 grade_iii, Cure model 1.19 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0126 NA NA NA
#> 2 grade_ii, Survival model 0.118 NA NA NA
#> 3 grade_iii, Survival model 0.0784 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.83727 -0.02394 0.26241 1.18860
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 251.5
#> Residual Deviance: 238.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.83727352 -0.02394213 0.26240742 1.18859904
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01264571 0.11827246 0.07843804
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.4384631994 0.2217730963 0.8874427318 0.0474496926 0.5535251682
#> [6] 0.0631905926 0.1850013594 0.8406352954 0.9512891473 0.7501053783
#> [11] 0.0180523578 0.6083093486 0.7797646004 0.2414393041 0.2925540321
#> [16] 0.0750871258 0.0474496926 0.1676800412 0.9191844399 0.8252285275
#> [21] 0.9675203810 0.5006269203 0.1939364762 0.3445169446 0.5808267326
#> [26] 0.1433086472 0.7501053783 0.0750871258 0.1069301366 0.3671381369
#> [31] 0.0474496926 0.6642667768 0.9032355995 0.9675203810 0.5006269203
#> [36] 0.0631905926 0.4384631994 0.3787106232 0.3904328373 0.6642667768
#> [41] 0.0325271517 0.3904328373 0.6642667768 0.0105924348 0.4384631994
#> [46] 0.2715960668 0.2925540321 0.0105924348 0.1279430570 0.1069301366
#> [51] 0.5400600330 0.1592625123 0.0750871258 0.2925540321 0.6361444936
#> [56] 0.2414393041 0.7797646004 0.0011681976 0.1433086472 0.4140698594
#> [61] 0.2612701373 0.0180523578 0.0422340946 0.0048458272 0.0011681976
#> [66] 0.2715960668 0.7063342365 0.0048458272 0.0180523578 0.2030107778
#> [71] 0.4876762950 0.1762578435 0.8717372525 0.1069301366 0.9352051333
#> [76] 0.0372757589 0.2030107778 0.0002086663 0.7353799916 0.5671185333
#> [81] 0.8406352954 0.4384631994 0.4261751346 0.0750871258 0.5266907183
#> [86] 0.2314966497 0.0180523578 0.3557564334 0.2925540321 0.6083093486
#> [91] 0.2925540321 0.1355042226 0.0998544564 0.6361444936 0.5808267326
#> [96] 0.8099115441 0.7208005516 0.0000000000 0.0000000000 0.0000000000
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000
#>
#> $Time
#> 18 41 187 136 57 153 76 145 77 107 63 155 159
#> 15.21 18.02 9.92 21.83 14.46 21.33 19.22 10.07 7.27 11.18 22.77 13.08 10.55
#> 117 85 99 136.1 170 149 61 25 180 8 5 60 166
#> 17.46 16.44 21.19 21.83 19.54 8.37 10.12 6.32 14.82 18.43 16.43 13.15 19.98
#> 107.1 36 32 100 136.2 154 16 25.1 180.1 153.1 18.1 26 6
#> 11.18 21.19 20.90 16.07 21.83 12.63 8.71 6.32 14.82 21.33 15.21 15.77 15.64
#> 154.1 15 6.1 154.2 92 18.2 130 192 92.1 128 32.1 96 105
#> 12.63 22.68 15.64 12.63 22.92 15.21 16.47 16.44 22.92 20.35 20.90 14.54 19.75
#> 36.1 192.1 14 117.1 159.1 168 166.1 39 23 63.1 175 129 168.1
#> 21.19 16.44 12.89 17.46 10.55 23.72 19.98 15.59 16.92 22.77 21.91 23.41 23.72
#> 130.1 56 129.1 63.2 51 157 58 101 32.2 70 194 51.1 78
#> 16.47 12.21 23.41 22.77 18.23 15.10 19.34 9.97 20.90 7.38 22.40 18.23 23.88
#> 43 81 145.1 18.3 29 36.2 133 110 63.3 188 192.2 155.1 192.3
#> 12.10 14.06 10.07 15.21 15.45 21.19 14.65 17.56 22.77 16.16 16.44 13.08 16.44
#> 158 90 14.1 60.1 10 49 65 17 146 185 27 156 200
#> 20.14 20.94 12.89 13.15 10.53 12.19 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 182 11 28 152 27.1 7 173 9 62 35 54 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 193 67.1 193.1 151 35.1 48 121 137 28.1 191 186 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 178 22 87 138 165 142 31 109 137.1 138.1 135 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 186.1 120 62.1 137.2 176 182.1 200.1 135.1 62.2 142.1 143 200.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 102 28.2 65.1 131 64 160 137.3 102.1 27.2 165.1 33 67.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.2 82 163.1 119 132 11.1 84 174 31.1 22.1 148 137.4 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[48]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003581913 0.725541277 0.822086982
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.142878663 -0.001864353 0.089763217
#> grade_iii, Cure model
#> 0.252166218
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 169 22.41 1 46 0 0
#> 100 16.07 1 60 0 0
#> 70 7.38 1 30 1 0
#> 70.1 7.38 1 30 1 0
#> 8 18.43 1 32 0 0
#> 153 21.33 1 55 1 0
#> 167 15.55 1 56 1 0
#> 199 19.81 1 NA 0 1
#> 88 18.37 1 47 0 0
#> 199.1 19.81 1 NA 0 1
#> 66 22.13 1 53 0 0
#> 85 16.44 1 36 0 0
#> 86 23.81 1 58 0 1
#> 105 19.75 1 60 0 0
#> 55 19.34 1 69 0 1
#> 184 17.77 1 38 0 0
#> 29 15.45 1 68 1 0
#> 169.1 22.41 1 46 0 0
#> 183 9.24 1 67 1 0
#> 157 15.10 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 169.2 22.41 1 46 0 0
#> 88.1 18.37 1 47 0 0
#> 133 14.65 1 57 0 0
#> 40 18.00 1 28 1 0
#> 153.1 21.33 1 55 1 0
#> 43 12.10 1 61 0 1
#> 43.1 12.10 1 61 0 1
#> 36 21.19 1 48 0 1
#> 15 22.68 1 48 0 0
#> 43.2 12.10 1 61 0 1
#> 155 13.08 1 26 0 0
#> 106 16.67 1 49 1 0
#> 124 9.73 1 NA 1 0
#> 124.1 9.73 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 41 18.02 1 40 1 0
#> 190 20.81 1 42 1 0
#> 60 13.15 1 38 1 0
#> 158 20.14 1 74 1 0
#> 51 18.23 1 83 0 1
#> 23 16.92 1 61 0 0
#> 192 16.44 1 31 1 0
#> 181 16.46 1 45 0 1
#> 78 23.88 1 43 0 0
#> 14 12.89 1 21 0 0
#> 101 9.97 1 10 0 1
#> 114 13.68 1 NA 0 0
#> 169.3 22.41 1 46 0 0
#> 125 15.65 1 67 1 0
#> 89 11.44 1 NA 0 0
#> 78.1 23.88 1 43 0 0
#> 125.1 15.65 1 67 1 0
#> 125.2 15.65 1 67 1 0
#> 61 10.12 1 36 0 1
#> 78.2 23.88 1 43 0 0
#> 110 17.56 1 65 0 1
#> 24 23.89 1 38 0 0
#> 129 23.41 1 53 1 0
#> 79 16.23 1 54 1 0
#> 10 10.53 1 34 0 0
#> 57 14.46 1 45 0 1
#> 32 20.90 1 37 1 0
#> 106.1 16.67 1 49 1 0
#> 70.2 7.38 1 30 1 0
#> 99 21.19 1 38 0 1
#> 58 19.34 1 39 0 0
#> 91.1 5.33 1 61 0 1
#> 184.1 17.77 1 38 0 0
#> 154 12.63 1 20 1 0
#> 16 8.71 1 71 0 1
#> 197 21.60 1 69 1 0
#> 81 14.06 1 34 0 0
#> 41.1 18.02 1 40 1 0
#> 155.1 13.08 1 26 0 0
#> 25 6.32 1 34 1 0
#> 124.2 9.73 1 NA 1 0
#> 153.2 21.33 1 55 1 0
#> 76 19.22 1 54 0 1
#> 78.3 23.88 1 43 0 0
#> 5 16.43 1 51 0 1
#> 99.1 21.19 1 38 0 1
#> 16.1 8.71 1 71 0 1
#> 41.2 18.02 1 40 1 0
#> 169.4 22.41 1 46 0 0
#> 10.1 10.53 1 34 0 0
#> 171 16.57 1 41 0 1
#> 107 11.18 1 54 1 0
#> 50.1 10.02 1 NA 1 0
#> 88.2 18.37 1 47 0 0
#> 199.2 19.81 1 NA 0 1
#> 181.1 16.46 1 45 0 1
#> 77 7.27 1 67 0 1
#> 183.1 9.24 1 67 1 0
#> 69 23.23 1 25 0 1
#> 37 12.52 1 57 1 0
#> 24.1 23.89 1 38 0 0
#> 149 8.37 1 33 1 0
#> 32.1 20.90 1 37 1 0
#> 108 18.29 1 39 0 1
#> 6 15.64 1 39 0 0
#> 68 20.62 1 44 0 0
#> 77.1 7.27 1 67 0 1
#> 158.1 20.14 1 74 1 0
#> 199.3 19.81 1 NA 0 1
#> 123 13.00 1 44 1 0
#> 139 21.49 1 63 1 0
#> 85.1 16.44 1 36 0 0
#> 56 12.21 1 60 0 0
#> 197.1 21.60 1 69 1 0
#> 158.2 20.14 1 74 1 0
#> 181.2 16.46 1 45 0 1
#> 163 24.00 0 66 0 0
#> 151 24.00 0 42 0 0
#> 62 24.00 0 71 0 0
#> 64 24.00 0 43 0 0
#> 48 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 102 24.00 0 49 0 0
#> 17.1 24.00 0 38 0 1
#> 62.1 24.00 0 71 0 0
#> 121 24.00 0 57 1 0
#> 160 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 191 24.00 0 60 0 1
#> 162 24.00 0 51 0 0
#> 160.1 24.00 0 31 1 0
#> 62.2 24.00 0 71 0 0
#> 126 24.00 0 48 0 0
#> 48.1 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 31 24.00 0 36 0 1
#> 31.1 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 48.2 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 20 24.00 0 46 1 0
#> 200 24.00 0 64 0 0
#> 122 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 62.3 24.00 0 71 0 0
#> 83 24.00 0 6 0 0
#> 198 24.00 0 66 0 1
#> 62.4 24.00 0 71 0 0
#> 147 24.00 0 76 1 0
#> 109 24.00 0 48 0 0
#> 112 24.00 0 61 0 0
#> 160.2 24.00 0 31 1 0
#> 83.1 24.00 0 6 0 0
#> 98 24.00 0 34 1 0
#> 34 24.00 0 36 0 0
#> 104 24.00 0 50 1 0
#> 137 24.00 0 45 1 0
#> 161 24.00 0 45 0 0
#> 17.2 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 11 24.00 0 42 0 1
#> 19 24.00 0 57 0 1
#> 126.1 24.00 0 48 0 0
#> 65 24.00 0 57 1 0
#> 87 24.00 0 27 0 0
#> 186 24.00 0 45 1 0
#> 28 24.00 0 67 1 0
#> 22 24.00 0 52 1 0
#> 186.1 24.00 0 45 1 0
#> 46 24.00 0 71 0 0
#> 21 24.00 0 47 0 0
#> 83.2 24.00 0 6 0 0
#> 126.2 24.00 0 48 0 0
#> 146 24.00 0 63 1 0
#> 143 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 178 24.00 0 52 1 0
#> 11.1 24.00 0 42 0 1
#> 185 24.00 0 44 1 0
#> 102.1 24.00 0 49 0 0
#> 116 24.00 0 58 0 1
#> 98.1 24.00 0 34 1 0
#> 198.1 24.00 0 66 0 1
#> 54 24.00 0 53 1 0
#> 161.1 24.00 0 45 0 0
#> 103 24.00 0 56 1 0
#> 198.2 24.00 0 66 0 1
#> 2 24.00 0 9 0 0
#> 46.1 24.00 0 71 0 0
#> 74 24.00 0 43 0 1
#> 135 24.00 0 58 1 0
#> 116.1 24.00 0 58 0 1
#> 147.1 24.00 0 76 1 0
#> 65.1 24.00 0 57 1 0
#> 103.1 24.00 0 56 1 0
#> 46.2 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 62.5 24.00 0 71 0 0
#> 73 24.00 0 NA 0 1
#> 178.1 24.00 0 52 1 0
#> 94.1 24.00 0 51 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.143 NA NA NA
#> 2 age, Cure model -0.00186 NA NA NA
#> 3 grade_ii, Cure model 0.0898 NA NA NA
#> 4 grade_iii, Cure model 0.252 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00358 NA NA NA
#> 2 grade_ii, Survival model 0.726 NA NA NA
#> 3 grade_iii, Survival model 0.822 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.142879 -0.001864 0.089763 0.252166
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 259.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.142878663 -0.001864353 0.089763217 0.252166218
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003581913 0.725541277 0.822086982
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.17917227 0.70217026 0.94529337 0.94529337 0.48082420 0.30165621
#> [7] 0.74188857 0.49057719 0.24540836 0.66136514 0.11594686 0.44142141
#> [13] 0.45147957 0.57471240 0.74979941 0.17917227 0.90961731 0.75765889
#> [19] 0.17917227 0.49057719 0.76553104 0.56569626 0.30165621 0.85060360
#> [25] 0.85060360 0.33754712 0.16443906 0.85060360 0.79681186 0.61058164
#> [31] 0.98653346 0.53870902 0.39113959 0.78905214 0.41205572 0.52917499
#> [37] 0.60161495 0.66136514 0.63666995 0.05352295 0.81999840 0.90232686
#> [43] 0.17917227 0.71030230 0.05352295 0.71030230 0.71030230 0.89496532
#> [49] 0.05352295 0.59267442 0.01701847 0.13368987 0.69405639 0.88018169
#> [55] 0.77341816 0.37011151 0.61058164 0.94529337 0.33754712 0.45147957
#> [61] 0.98653346 0.57471240 0.82771966 0.92399630 0.26053229 0.78123066
#> [67] 0.53870902 0.79681186 0.97969948 0.30165621 0.47109259 0.05352295
#> [73] 0.68587534 0.33754712 0.92399630 0.53870902 0.17917227 0.88018169
#> [79] 0.62801077 0.87277290 0.49057719 0.63666995 0.96600026 0.90961731
#> [85] 0.14991218 0.83537502 0.01701847 0.93820628 0.37011151 0.51952095
#> [91] 0.73391906 0.40157780 0.96600026 0.41205572 0.81228239 0.28800712
#> [97] 0.66136514 0.84298266 0.26053229 0.41205572 0.63666995 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 169 100 70 70.1 8 153 167 88 66 85 86 105 55
#> 22.41 16.07 7.38 7.38 18.43 21.33 15.55 18.37 22.13 16.44 23.81 19.75 19.34
#> 184 29 169.1 183 157 169.2 88.1 133 40 153.1 43 43.1 36
#> 17.77 15.45 22.41 9.24 15.10 22.41 18.37 14.65 18.00 21.33 12.10 12.10 21.19
#> 15 43.2 155 106 91 41 190 60 158 51 23 192 181
#> 22.68 12.10 13.08 16.67 5.33 18.02 20.81 13.15 20.14 18.23 16.92 16.44 16.46
#> 78 14 101 169.3 125 78.1 125.1 125.2 61 78.2 110 24 129
#> 23.88 12.89 9.97 22.41 15.65 23.88 15.65 15.65 10.12 23.88 17.56 23.89 23.41
#> 79 10 57 32 106.1 70.2 99 58 91.1 184.1 154 16 197
#> 16.23 10.53 14.46 20.90 16.67 7.38 21.19 19.34 5.33 17.77 12.63 8.71 21.60
#> 81 41.1 155.1 25 153.2 76 78.3 5 99.1 16.1 41.2 169.4 10.1
#> 14.06 18.02 13.08 6.32 21.33 19.22 23.88 16.43 21.19 8.71 18.02 22.41 10.53
#> 171 107 88.2 181.1 77 183.1 69 37 24.1 149 32.1 108 6
#> 16.57 11.18 18.37 16.46 7.27 9.24 23.23 12.52 23.89 8.37 20.90 18.29 15.64
#> 68 77.1 158.1 123 139 85.1 56 197.1 158.2 181.2 163 151 62
#> 20.62 7.27 20.14 13.00 21.49 16.44 12.21 21.60 20.14 16.46 24.00 24.00 24.00
#> 64 48 17 102 17.1 62.1 121 160 182 191 162 160.1 62.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 48.1 120 176 31 31.1 75 48.2 94 20 200 122 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 62.3 83 198 62.4 147 109 112 160.2 83.1 98 34 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 161 17.2 141 80 11 19 126.1 65 87 186 28 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.1 46 21 83.2 126.2 146 143 27 178 11.1 185 102.1 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 198.1 54 161.1 103 198.2 2 46.1 74 135 116.1 147.1 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.1 46.2 173 62.5 178.1 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[49]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00408644 0.76556474 0.35778973
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.289482856 0.004569356 0.261205858
#> grade_iii, Cure model
#> 0.615733806
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 199 19.81 1 NA 0 1
#> 16 8.71 1 71 0 1
#> 6 15.64 1 39 0 0
#> 32 20.90 1 37 1 0
#> 77 7.27 1 67 0 1
#> 78 23.88 1 43 0 0
#> 106 16.67 1 49 1 0
#> 61 10.12 1 36 0 1
#> 117 17.46 1 26 0 1
#> 60 13.15 1 38 1 0
#> 25 6.32 1 34 1 0
#> 100 16.07 1 60 0 0
#> 91 5.33 1 61 0 1
#> 154 12.63 1 20 1 0
#> 181 16.46 1 45 0 1
#> 4 17.64 1 NA 0 1
#> 68 20.62 1 44 0 0
#> 167 15.55 1 56 1 0
#> 79 16.23 1 54 1 0
#> 140 12.68 1 59 1 0
#> 100.1 16.07 1 60 0 0
#> 30 17.43 1 78 0 0
#> 179 18.63 1 42 0 0
#> 140.1 12.68 1 59 1 0
#> 61.1 10.12 1 36 0 1
#> 158 20.14 1 74 1 0
#> 164 23.60 1 76 0 1
#> 159 10.55 1 50 0 1
#> 130 16.47 1 53 0 1
#> 175 21.91 1 43 0 0
#> 157 15.10 1 47 0 0
#> 192 16.44 1 31 1 0
#> 58 19.34 1 39 0 0
#> 139 21.49 1 63 1 0
#> 49 12.19 1 48 1 0
#> 124 9.73 1 NA 1 0
#> 10 10.53 1 34 0 0
#> 199.1 19.81 1 NA 0 1
#> 113 22.86 1 34 0 0
#> 79.1 16.23 1 54 1 0
#> 183 9.24 1 67 1 0
#> 78.1 23.88 1 43 0 0
#> 134 17.81 1 47 1 0
#> 128 20.35 1 35 0 1
#> 188 16.16 1 46 0 1
#> 117.1 17.46 1 26 0 1
#> 70 7.38 1 30 1 0
#> 167.1 15.55 1 56 1 0
#> 66 22.13 1 53 0 0
#> 140.2 12.68 1 59 1 0
#> 123 13.00 1 44 1 0
#> 81 14.06 1 34 0 0
#> 189 10.51 1 NA 1 0
#> 117.2 17.46 1 26 0 1
#> 13 14.34 1 54 0 1
#> 123.1 13.00 1 44 1 0
#> 58.1 19.34 1 39 0 0
#> 170 19.54 1 43 0 1
#> 32.1 20.90 1 37 1 0
#> 29 15.45 1 68 1 0
#> 158.1 20.14 1 74 1 0
#> 18 15.21 1 49 1 0
#> 42 12.43 1 49 0 1
#> 77.1 7.27 1 67 0 1
#> 189.1 10.51 1 NA 1 0
#> 25.1 6.32 1 34 1 0
#> 79.2 16.23 1 54 1 0
#> 164.1 23.60 1 76 0 1
#> 108 18.29 1 39 0 1
#> 63 22.77 1 31 1 0
#> 114 13.68 1 NA 0 0
#> 41 18.02 1 40 1 0
#> 153 21.33 1 55 1 0
#> 175.1 21.91 1 43 0 0
#> 111 17.45 1 47 0 1
#> 140.3 12.68 1 59 1 0
#> 155 13.08 1 26 0 0
#> 68.1 20.62 1 44 0 0
#> 8 18.43 1 32 0 0
#> 52 10.42 1 52 0 1
#> 164.2 23.60 1 76 0 1
#> 41.1 18.02 1 40 1 0
#> 128.1 20.35 1 35 0 1
#> 10.1 10.53 1 34 0 0
#> 188.1 16.16 1 46 0 1
#> 113.1 22.86 1 34 0 0
#> 133 14.65 1 57 0 0
#> 99 21.19 1 38 0 1
#> 157.1 15.10 1 47 0 0
#> 157.2 15.10 1 47 0 0
#> 150 20.33 1 48 0 0
#> 6.1 15.64 1 39 0 0
#> 128.2 20.35 1 35 0 1
#> 183.1 9.24 1 67 1 0
#> 78.2 23.88 1 43 0 0
#> 5 16.43 1 51 0 1
#> 49.1 12.19 1 48 1 0
#> 86 23.81 1 58 0 1
#> 14 12.89 1 21 0 0
#> 171 16.57 1 41 0 1
#> 99.1 21.19 1 38 0 1
#> 69 23.23 1 25 0 1
#> 181.1 16.46 1 45 0 1
#> 45 17.42 1 54 0 1
#> 30.1 17.43 1 78 0 0
#> 159.1 10.55 1 50 0 1
#> 150.1 20.33 1 48 0 0
#> 154.1 12.63 1 20 1 0
#> 43 12.10 1 61 0 1
#> 96 14.54 1 33 0 1
#> 45.1 17.42 1 54 0 1
#> 150.2 20.33 1 48 0 0
#> 120 24.00 0 68 0 1
#> 22 24.00 0 52 1 0
#> 28 24.00 0 67 1 0
#> 28.1 24.00 0 67 1 0
#> 115 24.00 0 NA 1 0
#> 102 24.00 0 49 0 0
#> 178 24.00 0 52 1 0
#> 152 24.00 0 36 0 1
#> 46 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 112 24.00 0 61 0 0
#> 135 24.00 0 58 1 0
#> 28.2 24.00 0 67 1 0
#> 143 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 64 24.00 0 43 0 0
#> 20 24.00 0 46 1 0
#> 34 24.00 0 36 0 0
#> 112.1 24.00 0 61 0 0
#> 196 24.00 0 19 0 0
#> 182 24.00 0 35 0 0
#> 191 24.00 0 60 0 1
#> 73 24.00 0 NA 0 1
#> 196.1 24.00 0 19 0 0
#> 48 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 83 24.00 0 6 0 0
#> 120.1 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#> 34.1 24.00 0 36 0 0
#> 122 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 72 24.00 0 40 0 1
#> 142 24.00 0 53 0 0
#> 48.1 24.00 0 31 1 0
#> 83.1 24.00 0 6 0 0
#> 193 24.00 0 45 0 1
#> 33 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 22.1 24.00 0 52 1 0
#> 75 24.00 0 21 1 0
#> 160 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 17 24.00 0 38 0 1
#> 9.1 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 102.1 24.00 0 49 0 0
#> 109 24.00 0 48 0 0
#> 126 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 80 24.00 0 41 0 0
#> 174 24.00 0 49 1 0
#> 74 24.00 0 43 0 1
#> 165 24.00 0 47 0 0
#> 120.2 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 67 24.00 0 25 0 0
#> 31 24.00 0 36 0 1
#> 28.3 24.00 0 67 1 0
#> 84 24.00 0 39 0 1
#> 28.4 24.00 0 67 1 0
#> 137.1 24.00 0 45 1 0
#> 62 24.00 0 71 0 0
#> 94 24.00 0 51 0 1
#> 72.1 24.00 0 40 0 1
#> 19 24.00 0 57 0 1
#> 62.1 24.00 0 71 0 0
#> 19.1 24.00 0 57 0 1
#> 165.1 24.00 0 47 0 0
#> 126.1 24.00 0 48 0 0
#> 198 24.00 0 66 0 1
#> 74.1 24.00 0 43 0 1
#> 2 24.00 0 9 0 0
#> 67.1 24.00 0 25 0 0
#> 3 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 200 24.00 0 64 0 0
#> 84.1 24.00 0 39 0 1
#> 172 24.00 0 41 0 0
#> 87.1 24.00 0 27 0 0
#> 75.1 24.00 0 21 1 0
#> 75.2 24.00 0 21 1 0
#> 109.1 24.00 0 48 0 0
#> 198.1 24.00 0 66 0 1
#> 38 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.289 NA NA NA
#> 2 age, Cure model 0.00457 NA NA NA
#> 3 grade_ii, Cure model 0.261 NA NA NA
#> 4 grade_iii, Cure model 0.616 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00409 NA NA NA
#> 2 grade_ii, Survival model 0.766 NA NA NA
#> 3 grade_iii, Survival model 0.358 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.289483 0.004569 0.261206 0.615734
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 259.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.289482856 0.004569356 0.261205858 0.615733806
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00408644 0.76556474 0.35778973
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.94727462 0.64667925 0.23533744 0.96251562 0.01487239 0.52204960
#> [7] 0.91662923 0.44741119 0.75752748 0.97762107 0.62931518 0.99252587
#> [13] 0.83098776 0.54988619 0.25603674 0.66411230 0.58621352 0.79919537
#> [19] 0.62931518 0.48453825 0.38783030 0.79919537 0.91662923 0.33768538
#> [25] 0.06445453 0.87793195 0.54063472 0.16408295 0.69823363 0.56811801
#> [31] 0.36777288 0.18890142 0.85464104 0.89338087 0.11346896 0.58621352
#> [37] 0.93203192 0.01487239 0.43779576 0.27701593 0.61205470 0.44741119
#> [43] 0.95492255 0.66411230 0.15148843 0.79919537 0.77439480 0.74901889
#> [49] 0.44741119 0.74052282 0.77439480 0.36777288 0.35768588 0.23533744
#> [55] 0.68122625 0.33768538 0.68976978 0.84674037 0.96251562 0.97762107
#> [61] 0.58621352 0.06445453 0.40827051 0.13909502 0.41845071 0.20119441
#> [67] 0.16408295 0.47514226 0.79919537 0.76595646 0.25603674 0.39803432
#> [73] 0.90886453 0.06445453 0.41845071 0.27701593 0.89338087 0.61205470
#> [79] 0.11346896 0.72347719 0.21297154 0.69823363 0.69823363 0.30708281
#> [85] 0.64667925 0.27701593 0.93203192 0.01487239 0.57717719 0.85464104
#> [91] 0.04898955 0.79089475 0.53135919 0.21297154 0.10026197 0.54988619
#> [97] 0.50334524 0.48453825 0.87793195 0.30708281 0.83098776 0.87015039
#> [103] 0.73201239 0.50334524 0.30708281 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 16 6 32 77 78 106 61 117 60 25 100 91 154
#> 8.71 15.64 20.90 7.27 23.88 16.67 10.12 17.46 13.15 6.32 16.07 5.33 12.63
#> 181 68 167 79 140 100.1 30 179 140.1 61.1 158 164 159
#> 16.46 20.62 15.55 16.23 12.68 16.07 17.43 18.63 12.68 10.12 20.14 23.60 10.55
#> 130 175 157 192 58 139 49 10 113 79.1 183 78.1 134
#> 16.47 21.91 15.10 16.44 19.34 21.49 12.19 10.53 22.86 16.23 9.24 23.88 17.81
#> 128 188 117.1 70 167.1 66 140.2 123 81 117.2 13 123.1 58.1
#> 20.35 16.16 17.46 7.38 15.55 22.13 12.68 13.00 14.06 17.46 14.34 13.00 19.34
#> 170 32.1 29 158.1 18 42 77.1 25.1 79.2 164.1 108 63 41
#> 19.54 20.90 15.45 20.14 15.21 12.43 7.27 6.32 16.23 23.60 18.29 22.77 18.02
#> 153 175.1 111 140.3 155 68.1 8 52 164.2 41.1 128.1 10.1 188.1
#> 21.33 21.91 17.45 12.68 13.08 20.62 18.43 10.42 23.60 18.02 20.35 10.53 16.16
#> 113.1 133 99 157.1 157.2 150 6.1 128.2 183.1 78.2 5 49.1 86
#> 22.86 14.65 21.19 15.10 15.10 20.33 15.64 20.35 9.24 23.88 16.43 12.19 23.81
#> 14 171 99.1 69 181.1 45 30.1 159.1 150.1 154.1 43 96 45.1
#> 12.89 16.57 21.19 23.23 16.46 17.42 17.43 10.55 20.33 12.63 12.10 14.54 17.42
#> 150.2 120 22 28 28.1 102 178 152 46 173 112 135 28.2
#> 20.33 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 148 64 20 34 112.1 196 182 191 196.1 48 65 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 186 95 34.1 122 9 147 72 142 48.1 83.1 193 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 22.1 75 160 87 17 9.1 71 102.1 109 126 141 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 174 74 165 120.2 53 67 31 28.3 84 28.4 137.1 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 72.1 19 62.1 19.1 165.1 126.1 198 74.1 2 67.1 3 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 84.1 172 87.1 75.1 75.2 109.1 198.1 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[50]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003958107 0.570474095 0.057135078
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.72859877 0.01417669 0.27034415
#> grade_iii, Cure model
#> 0.59558244
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 39 15.59 1 37 0 1
#> 136 21.83 1 43 0 1
#> 166 19.98 1 48 0 0
#> 149 8.37 1 33 1 0
#> 18 15.21 1 49 1 0
#> 91 5.33 1 61 0 1
#> 37 12.52 1 57 1 0
#> 52 10.42 1 52 0 1
#> 69 23.23 1 25 0 1
#> 107 11.18 1 54 1 0
#> 154 12.63 1 20 1 0
#> 40 18.00 1 28 1 0
#> 130 16.47 1 53 0 1
#> 111 17.45 1 47 0 1
#> 195 11.76 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 139 21.49 1 63 1 0
#> 29 15.45 1 68 1 0
#> 14 12.89 1 21 0 0
#> 51 18.23 1 83 0 1
#> 85 16.44 1 36 0 0
#> 111.1 17.45 1 47 0 1
#> 59 10.16 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 57 14.46 1 45 0 1
#> 39.1 15.59 1 37 0 1
#> 187 9.92 1 39 1 0
#> 157 15.10 1 47 0 0
#> 195.1 11.76 1 NA 1 0
#> 69.1 23.23 1 25 0 1
#> 51.1 18.23 1 83 0 1
#> 157.1 15.10 1 47 0 0
#> 49 12.19 1 48 1 0
#> 133 14.65 1 57 0 0
#> 97 19.14 1 65 0 1
#> 43 12.10 1 61 0 1
#> 90 20.94 1 50 0 1
#> 106 16.67 1 49 1 0
#> 197 21.60 1 69 1 0
#> 113 22.86 1 34 0 0
#> 107.1 11.18 1 54 1 0
#> 124 9.73 1 NA 1 0
#> 187.1 9.92 1 39 1 0
#> 14.1 12.89 1 21 0 0
#> 164 23.60 1 76 0 1
#> 69.2 23.23 1 25 0 1
#> 29.1 15.45 1 68 1 0
#> 30 17.43 1 78 0 0
#> 36 21.19 1 48 0 1
#> 55 19.34 1 69 0 1
#> 43.1 12.10 1 61 0 1
#> 139.1 21.49 1 63 1 0
#> 177.1 12.53 1 75 0 0
#> 51.2 18.23 1 83 0 1
#> 78 23.88 1 43 0 0
#> 59.1 10.16 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 88 18.37 1 47 0 0
#> 14.2 12.89 1 21 0 0
#> 24 23.89 1 38 0 0
#> 129 23.41 1 53 1 0
#> 32 20.90 1 37 1 0
#> 76 19.22 1 54 0 1
#> 41 18.02 1 40 1 0
#> 153 21.33 1 55 1 0
#> 58 19.34 1 39 0 0
#> 99 21.19 1 38 0 1
#> 85.1 16.44 1 36 0 0
#> 5 16.43 1 51 0 1
#> 10 10.53 1 34 0 0
#> 187.2 9.92 1 39 1 0
#> 149.1 8.37 1 33 1 0
#> 13.1 14.34 1 54 0 1
#> 195.2 11.76 1 NA 1 0
#> 58.1 19.34 1 39 0 0
#> 43.2 12.10 1 61 0 1
#> 169 22.41 1 46 0 0
#> 110 17.56 1 65 0 1
#> 66 22.13 1 53 0 0
#> 10.1 10.53 1 34 0 0
#> 29.2 15.45 1 68 1 0
#> 175 21.91 1 43 0 0
#> 133.1 14.65 1 57 0 0
#> 106.1 16.67 1 49 1 0
#> 55.1 19.34 1 69 0 1
#> 15 22.68 1 48 0 0
#> 181 16.46 1 45 0 1
#> 136.1 21.83 1 43 0 1
#> 192 16.44 1 31 1 0
#> 113.1 22.86 1 34 0 0
#> 100 16.07 1 60 0 0
#> 49.1 12.19 1 48 1 0
#> 192.1 16.44 1 31 1 0
#> 170 19.54 1 43 0 1
#> 133.2 14.65 1 57 0 0
#> 164.1 23.60 1 76 0 1
#> 154.1 12.63 1 20 1 0
#> 56 12.21 1 60 0 0
#> 36.1 21.19 1 48 0 1
#> 26 15.77 1 49 0 1
#> 179 18.63 1 42 0 0
#> 88.1 18.37 1 47 0 0
#> 153.1 21.33 1 55 1 0
#> 56.1 12.21 1 60 0 0
#> 166.1 19.98 1 48 0 0
#> 110.1 17.56 1 65 0 1
#> 164.2 23.60 1 76 0 1
#> 18.1 15.21 1 49 1 0
#> 39.2 15.59 1 37 0 1
#> 40.1 18.00 1 28 1 0
#> 30.1 17.43 1 78 0 0
#> 106.2 16.67 1 49 1 0
#> 84 24.00 0 39 0 1
#> 200 24.00 0 64 0 0
#> 34 24.00 0 36 0 0
#> 11 24.00 0 42 0 1
#> 34.1 24.00 0 36 0 0
#> 87 24.00 0 27 0 0
#> 71 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 141 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 35 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 135 24.00 0 58 1 0
#> 131 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 17 24.00 0 38 0 1
#> 84.1 24.00 0 39 0 1
#> 146 24.00 0 63 1 0
#> 144 24.00 0 28 0 1
#> 27.1 24.00 0 63 1 0
#> 191 24.00 0 60 0 1
#> 109 24.00 0 48 0 0
#> 120 24.00 0 68 0 1
#> 2 24.00 0 9 0 0
#> 131.1 24.00 0 66 0 0
#> 141.1 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 146.1 24.00 0 63 1 0
#> 17.1 24.00 0 38 0 1
#> 35.1 24.00 0 51 0 0
#> 35.2 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 172 24.00 0 41 0 0
#> 19 24.00 0 57 0 1
#> 160 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 120.1 24.00 0 68 0 1
#> 173 24.00 0 19 0 1
#> 94 24.00 0 51 0 1
#> 35.3 24.00 0 51 0 0
#> 160.1 24.00 0 31 1 0
#> 160.2 24.00 0 31 1 0
#> 17.2 24.00 0 38 0 1
#> 172.1 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 135.1 24.00 0 58 1 0
#> 162 24.00 0 51 0 0
#> 143.1 24.00 0 51 0 0
#> 115.1 24.00 0 NA 1 0
#> 22 24.00 0 52 1 0
#> 82 24.00 0 34 0 0
#> 34.2 24.00 0 36 0 0
#> 34.3 24.00 0 36 0 0
#> 74 24.00 0 43 0 1
#> 82.1 24.00 0 34 0 0
#> 3 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 137 24.00 0 45 1 0
#> 122.1 24.00 0 66 0 0
#> 84.2 24.00 0 39 0 1
#> 142.1 24.00 0 53 0 0
#> 132 24.00 0 55 0 0
#> 121 24.00 0 57 1 0
#> 161 24.00 0 45 0 0
#> 38 24.00 0 31 1 0
#> 160.3 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 144.1 24.00 0 28 0 1
#> 2.1 24.00 0 9 0 0
#> 178.1 24.00 0 52 1 0
#> 12 24.00 0 63 0 0
#> 65 24.00 0 57 1 0
#> 71.1 24.00 0 51 0 0
#> 178.2 24.00 0 52 1 0
#> 84.3 24.00 0 39 0 1
#> 156 24.00 0 50 1 0
#> 148 24.00 0 61 1 0
#> 193 24.00 0 45 0 1
#> 161.1 24.00 0 45 0 0
#> 35.4 24.00 0 51 0 0
#> 72.1 24.00 0 40 0 1
#> 115.2 24.00 0 NA 1 0
#> 152 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.729 NA NA NA
#> 2 age, Cure model 0.0142 NA NA NA
#> 3 grade_ii, Cure model 0.270 NA NA NA
#> 4 grade_iii, Cure model 0.596 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00396 NA NA NA
#> 2 grade_ii, Survival model 0.570 NA NA NA
#> 3 grade_iii, Survival model 0.0571 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.72860 0.01418 0.27034 0.59558
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.5
#> Residual Deviance: 257.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.72859877 0.01417669 0.27034415 0.59558244
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003958107 0.570474095 0.057135078
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.610205018 0.152268972 0.266732497 0.972866124 0.666423608 0.990918391
#> [7] 0.825055073 0.936331021 0.066835348 0.899393752 0.787771020 0.419882014
#> [13] 0.525343796 0.458198674 0.020341543 0.182836347 0.638531732 0.759637545
#> [19] 0.380569630 0.544608528 0.458198674 0.806357691 0.731385964 0.610205018
#> [25] 0.945635905 0.684912874 0.066835348 0.380569630 0.684912874 0.853113349
#> [31] 0.703487281 0.341534662 0.871625427 0.247821332 0.497073836 0.172578919
#> [37] 0.092852869 0.899393752 0.945635905 0.759637545 0.030534665 0.066835348
#> [43] 0.638531732 0.477531138 0.220402167 0.294855917 0.871625427 0.182836347
#> [49] 0.806357691 0.380569630 0.011310828 0.740820188 0.361075460 0.759637545
#> [55] 0.003537612 0.056949527 0.257368605 0.331835318 0.409963863 0.201987641
#> [61] 0.294855917 0.220402167 0.544608528 0.581615228 0.917838985 0.945635905
#> [67] 0.972866124 0.740820188 0.294855917 0.871625427 0.121563357 0.438964458
#> [73] 0.131660099 0.917838985 0.638531732 0.141905847 0.703487281 0.497073836
#> [79] 0.294855917 0.111604692 0.534966278 0.152268972 0.544608528 0.092852869
#> [85] 0.591117093 0.853113349 0.544608528 0.285354243 0.703487281 0.030534665
#> [91] 0.787771020 0.834413422 0.220402167 0.600651359 0.351284243 0.361075460
#> [97] 0.201987641 0.834413422 0.266732497 0.438964458 0.030534665 0.666423608
#> [103] 0.610205018 0.419882014 0.477531138 0.497073836 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 39 136 166 149 18 91 37 52 69 107 154 40 130
#> 15.59 21.83 19.98 8.37 15.21 5.33 12.52 10.42 23.23 11.18 12.63 18.00 16.47
#> 111 168 139 29 14 51 85 111.1 177 57 39.1 187 157
#> 17.45 23.72 21.49 15.45 12.89 18.23 16.44 17.45 12.53 14.46 15.59 9.92 15.10
#> 69.1 51.1 157.1 49 133 97 43 90 106 197 113 107.1 187.1
#> 23.23 18.23 15.10 12.19 14.65 19.14 12.10 20.94 16.67 21.60 22.86 11.18 9.92
#> 14.1 164 69.2 29.1 30 36 55 43.1 139.1 177.1 51.2 78 13
#> 12.89 23.60 23.23 15.45 17.43 21.19 19.34 12.10 21.49 12.53 18.23 23.88 14.34
#> 88 14.2 24 129 32 76 41 153 58 99 85.1 5 10
#> 18.37 12.89 23.89 23.41 20.90 19.22 18.02 21.33 19.34 21.19 16.44 16.43 10.53
#> 187.2 149.1 13.1 58.1 43.2 169 110 66 10.1 29.2 175 133.1 106.1
#> 9.92 8.37 14.34 19.34 12.10 22.41 17.56 22.13 10.53 15.45 21.91 14.65 16.67
#> 55.1 15 181 136.1 192 113.1 100 49.1 192.1 170 133.2 164.1 154.1
#> 19.34 22.68 16.46 21.83 16.44 22.86 16.07 12.19 16.44 19.54 14.65 23.60 12.63
#> 56 36.1 26 179 88.1 153.1 56.1 166.1 110.1 164.2 18.1 39.2 40.1
#> 12.21 21.19 15.77 18.63 18.37 21.33 12.21 19.98 17.56 23.60 15.21 15.59 18.00
#> 30.1 106.2 84 200 34 11 34.1 87 71 27 141 48 35
#> 17.43 16.67 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 33 135 131 118 119 17 84.1 146 144 27.1 191 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 2 131.1 141.1 72 146.1 17.1 35.1 35.2 112 172 19 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 142 62 120.1 173 94 35.3 160.1 160.2 17.2 172.1 198 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 143.1 22 82 34.2 34.3 74 82.1 3 178 137 122.1 84.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 132 121 161 38 160.3 104 144.1 2.1 178.1 12 65 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.2 84.3 156 148 193 161.1 35.4 72.1 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[51]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01689042 0.37866783 0.16797555
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.06012118 0.01604637 0.69576866
#> grade_iii, Cure model
#> 0.82992446
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 56 12.21 1 60 0 0
#> 139 21.49 1 63 1 0
#> 113 22.86 1 34 0 0
#> 93 10.33 1 52 0 1
#> 180 14.82 1 37 0 0
#> 134 17.81 1 47 1 0
#> 195 11.76 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 97 19.14 1 65 0 1
#> 42 12.43 1 49 0 1
#> 92 22.92 1 47 0 1
#> 129 23.41 1 53 1 0
#> 76 19.22 1 54 0 1
#> 157 15.10 1 47 0 0
#> 81 14.06 1 34 0 0
#> 97.1 19.14 1 65 0 1
#> 136 21.83 1 43 0 1
#> 197 21.60 1 69 1 0
#> 55 19.34 1 69 0 1
#> 150 20.33 1 48 0 0
#> 52 10.42 1 52 0 1
#> 164 23.60 1 76 0 1
#> 166 19.98 1 48 0 0
#> 154 12.63 1 20 1 0
#> 36 21.19 1 48 0 1
#> 134.1 17.81 1 47 1 0
#> 164.1 23.60 1 76 0 1
#> 70 7.38 1 30 1 0
#> 29 15.45 1 68 1 0
#> 168 23.72 1 70 0 0
#> 170 19.54 1 43 0 1
#> 183 9.24 1 67 1 0
#> 124 9.73 1 NA 1 0
#> 92.1 22.92 1 47 0 1
#> 70.1 7.38 1 30 1 0
#> 190 20.81 1 42 1 0
#> 155 13.08 1 26 0 0
#> 76.1 19.22 1 54 0 1
#> 63 22.77 1 31 1 0
#> 114 13.68 1 NA 0 0
#> 86 23.81 1 58 0 1
#> 194 22.40 1 38 0 1
#> 190.1 20.81 1 42 1 0
#> 61 10.12 1 36 0 1
#> 39 15.59 1 37 0 1
#> 40 18.00 1 28 1 0
#> 78 23.88 1 43 0 0
#> 139.1 21.49 1 63 1 0
#> 108 18.29 1 39 0 1
#> 149 8.37 1 33 1 0
#> 99 21.19 1 38 0 1
#> 158 20.14 1 74 1 0
#> 157.1 15.10 1 47 0 0
#> 127 3.53 1 62 0 1
#> 59 10.16 1 NA 1 0
#> 168.1 23.72 1 70 0 0
#> 45 17.42 1 54 0 1
#> 183.1 9.24 1 67 1 0
#> 189 10.51 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 43 12.10 1 61 0 1
#> 76.2 19.22 1 54 0 1
#> 26 15.77 1 49 0 1
#> 136.1 21.83 1 43 0 1
#> 194.1 22.40 1 38 0 1
#> 129.1 23.41 1 53 1 0
#> 18 15.21 1 49 1 0
#> 30 17.43 1 78 0 0
#> 157.2 15.10 1 47 0 0
#> 5 16.43 1 51 0 1
#> 14.1 12.89 1 21 0 0
#> 92.2 22.92 1 47 0 1
#> 197.1 21.60 1 69 1 0
#> 184 17.77 1 38 0 0
#> 59.1 10.16 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 78.1 23.88 1 43 0 0
#> 37 12.52 1 57 1 0
#> 56.1 12.21 1 60 0 0
#> 5.1 16.43 1 51 0 1
#> 59.2 10.16 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 57 14.46 1 45 0 1
#> 10 10.53 1 34 0 0
#> 101 9.97 1 10 0 1
#> 123 13.00 1 44 1 0
#> 23 16.92 1 61 0 0
#> 76.3 19.22 1 54 0 1
#> 149.1 8.37 1 33 1 0
#> 149.2 8.37 1 33 1 0
#> 140 12.68 1 59 1 0
#> 167 15.55 1 56 1 0
#> 30.1 17.43 1 78 0 0
#> 140.1 12.68 1 59 1 0
#> 58 19.34 1 39 0 0
#> 91 5.33 1 61 0 1
#> 99.1 21.19 1 38 0 1
#> 13 14.34 1 54 0 1
#> 32 20.90 1 37 1 0
#> 154.1 12.63 1 20 1 0
#> 6 15.64 1 39 0 0
#> 158.1 20.14 1 74 1 0
#> 32.1 20.90 1 37 1 0
#> 40.1 18.00 1 28 1 0
#> 166.1 19.98 1 48 0 0
#> 96 14.54 1 33 0 1
#> 77 7.27 1 67 0 1
#> 150.1 20.33 1 48 0 0
#> 140.2 12.68 1 59 1 0
#> 61.1 10.12 1 36 0 1
#> 10.1 10.53 1 34 0 0
#> 52.1 10.42 1 52 0 1
#> 161 24.00 0 45 0 0
#> 80 24.00 0 41 0 0
#> 7 24.00 0 37 1 0
#> 71 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 34 24.00 0 36 0 0
#> 115 24.00 0 NA 1 0
#> 82.1 24.00 0 34 0 0
#> 44 24.00 0 56 0 0
#> 11 24.00 0 42 0 1
#> 160 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 27 24.00 0 63 1 0
#> 161.1 24.00 0 45 0 0
#> 31 24.00 0 36 0 1
#> 193 24.00 0 45 0 1
#> 27.1 24.00 0 63 1 0
#> 193.1 24.00 0 45 0 1
#> 148 24.00 0 61 1 0
#> 84 24.00 0 39 0 1
#> 152 24.00 0 36 0 1
#> 80.1 24.00 0 41 0 0
#> 53 24.00 0 32 0 1
#> 116 24.00 0 58 0 1
#> 35 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 94 24.00 0 51 0 1
#> 80.2 24.00 0 41 0 0
#> 104 24.00 0 50 1 0
#> 67 24.00 0 25 0 0
#> 64 24.00 0 43 0 0
#> 193.2 24.00 0 45 0 1
#> 3 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 142 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 98 24.00 0 34 1 0
#> 119 24.00 0 17 0 0
#> 7.1 24.00 0 37 1 0
#> 31.1 24.00 0 36 0 1
#> 11.1 24.00 0 42 0 1
#> 53.1 24.00 0 32 0 1
#> 35.1 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 20 24.00 0 46 1 0
#> 87 24.00 0 27 0 0
#> 20.1 24.00 0 46 1 0
#> 33 24.00 0 53 0 0
#> 162 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 161.2 24.00 0 45 0 0
#> 146 24.00 0 63 1 0
#> 176 24.00 0 43 0 1
#> 165 24.00 0 47 0 0
#> 87.1 24.00 0 27 0 0
#> 3.1 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 33.1 24.00 0 53 0 0
#> 71.1 24.00 0 51 0 0
#> 20.2 24.00 0 46 1 0
#> 31.2 24.00 0 36 0 1
#> 82.2 24.00 0 34 0 0
#> 7.2 24.00 0 37 1 0
#> 34.1 24.00 0 36 0 0
#> 22 24.00 0 52 1 0
#> 19 24.00 0 57 0 1
#> 46 24.00 0 71 0 0
#> 53.2 24.00 0 32 0 1
#> 9 24.00 0 31 1 0
#> 148.1 24.00 0 61 1 0
#> 147 24.00 0 76 1 0
#> 165.1 24.00 0 47 0 0
#> 119.1 24.00 0 17 0 0
#> 200 24.00 0 64 0 0
#> 19.1 24.00 0 57 0 1
#> 80.3 24.00 0 41 0 0
#> 33.2 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 67.1 24.00 0 25 0 0
#> 191.1 24.00 0 60 0 1
#> 120.1 24.00 0 68 0 1
#> 172.1 24.00 0 41 0 0
#> 98.1 24.00 0 34 1 0
#> 174 24.00 0 49 1 0
#> 121 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.06 NA NA NA
#> 2 age, Cure model 0.0160 NA NA NA
#> 3 grade_ii, Cure model 0.696 NA NA NA
#> 4 grade_iii, Cure model 0.830 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0169 NA NA NA
#> 2 grade_ii, Survival model 0.379 NA NA NA
#> 3 grade_iii, Survival model 0.168 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06012 0.01605 0.69577 0.82992
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 255.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06012118 0.01604637 0.69576866 0.82992446
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01689042 0.37866783 0.16797555
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 6.565454e-01 4.850436e-02 1.844525e-02 7.601340e-01 4.433284e-01
#> [6] 2.392517e-01 8.224041e-01 1.948728e-01 6.423811e-01 1.066663e-02
#> [11] 6.364599e-03 1.631797e-01 4.074314e-01 4.940048e-01 1.948728e-01
#> [16] 3.215368e-02 3.987259e-02 1.481063e-01 1.013956e-01 7.297981e-01
#> [21] 3.017680e-03 1.268495e-01 6.009165e-01 6.310636e-02 2.392517e-01
#> [26] 3.017680e-03 9.178513e-01 3.840564e-01 1.123739e-03 1.407935e-01
#> [31] 8.381760e-01 1.066663e-02 9.178513e-01 8.986141e-02 5.070615e-01
#> [36] 1.631797e-01 2.176604e-02 5.533328e-04 2.515753e-02 8.986141e-02
#> [41] 7.756150e-01 3.613282e-01 2.213772e-01 7.000504e-05 4.850436e-02
#> [46] 2.123195e-01 8.700518e-01 6.310636e-02 1.137084e-01 4.074314e-01
#> [51] 9.832138e-01 1.123739e-03 2.867694e-01 8.381760e-01 5.335189e-01
#> [56] 6.853516e-01 1.631797e-01 3.391748e-01 3.215368e-02 2.515753e-02
#> [61] 6.364599e-03 3.956815e-01 2.670950e-01 4.074314e-01 3.178748e-01
#> [66] 5.335189e-01 1.066663e-02 3.987259e-02 2.575922e-01 3.073975e-01
#> [71] 7.000504e-05 6.283661e-01 6.565454e-01 3.178748e-01 5.797472e-02
#> [76] 4.683688e-01 7.000903e-01 8.067057e-01 5.202388e-01 2.969683e-01
#> [81] 1.631797e-01 8.700518e-01 8.700518e-01 5.601394e-01 3.726173e-01
#> [86] 2.670950e-01 5.601394e-01 1.481063e-01 9.665936e-01 6.310636e-02
#> [91] 4.810972e-01 7.873094e-02 6.009165e-01 3.501670e-01 1.137084e-01
#> [96] 7.873094e-02 2.213772e-01 1.268495e-01 4.557931e-01 9.501368e-01
#> [101] 1.013956e-01 5.601394e-01 7.756150e-01 7.000903e-01 7.297981e-01
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 56 139 113 93 180 134 187 97 42 92 129 76 157
#> 12.21 21.49 22.86 10.33 14.82 17.81 9.92 19.14 12.43 22.92 23.41 19.22 15.10
#> 81 97.1 136 197 55 150 52 164 166 154 36 134.1 164.1
#> 14.06 19.14 21.83 21.60 19.34 20.33 10.42 23.60 19.98 12.63 21.19 17.81 23.60
#> 70 29 168 170 183 92.1 70.1 190 155 76.1 63 86 194
#> 7.38 15.45 23.72 19.54 9.24 22.92 7.38 20.81 13.08 19.22 22.77 23.81 22.40
#> 190.1 61 39 40 78 139.1 108 149 99 158 157.1 127 168.1
#> 20.81 10.12 15.59 18.00 23.88 21.49 18.29 8.37 21.19 20.14 15.10 3.53 23.72
#> 45 183.1 14 43 76.2 26 136.1 194.1 129.1 18 30 157.2 5
#> 17.42 9.24 12.89 12.10 19.22 15.77 21.83 22.40 23.41 15.21 17.43 15.10 16.43
#> 14.1 92.2 197.1 184 192 78.1 37 56.1 5.1 153 57 10 101
#> 12.89 22.92 21.60 17.77 16.44 23.88 12.52 12.21 16.43 21.33 14.46 10.53 9.97
#> 123 23 76.3 149.1 149.2 140 167 30.1 140.1 58 91 99.1 13
#> 13.00 16.92 19.22 8.37 8.37 12.68 15.55 17.43 12.68 19.34 5.33 21.19 14.34
#> 32 154.1 6 158.1 32.1 40.1 166.1 96 77 150.1 140.2 61.1 10.1
#> 20.90 12.63 15.64 20.14 20.90 18.00 19.98 14.54 7.27 20.33 12.68 10.12 10.53
#> 52.1 161 80 7 71 82 34 82.1 44 11 160 109 27
#> 10.42 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 31 193 27.1 193.1 148 84 152 80.1 53 116 35 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 80.2 104 67 64 193.2 3 172 142 28 98 119 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 11.1 53.1 35.1 191 20 87 20.1 33 162 185 161.2 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 165 87.1 3.1 120 143 132 33.1 71.1 20.2 31.2 82.2 7.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 22 19 46 53.2 9 148.1 147 165.1 119.1 200 19.1 80.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.2 38 47 67.1 191.1 120.1 172.1 98.1 174 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[52]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008995778 0.523250133 0.567072598
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.693367882 0.009625798 0.102417881
#> grade_iii, Cure model
#> 1.271254276
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 52 10.42 1 52 0 1
#> 183 9.24 1 67 1 0
#> 55 19.34 1 69 0 1
#> 179 18.63 1 42 0 0
#> 66 22.13 1 53 0 0
#> 51 18.23 1 83 0 1
#> 63 22.77 1 31 1 0
#> 89 11.44 1 NA 0 0
#> 91 5.33 1 61 0 1
#> 190 20.81 1 42 1 0
#> 123 13.00 1 44 1 0
#> 76 19.22 1 54 0 1
#> 123.1 13.00 1 44 1 0
#> 101 9.97 1 10 0 1
#> 85 16.44 1 36 0 0
#> 133 14.65 1 57 0 0
#> 89.1 11.44 1 NA 0 0
#> 197 21.60 1 69 1 0
#> 93 10.33 1 52 0 1
#> 15 22.68 1 48 0 0
#> 29 15.45 1 68 1 0
#> 63.1 22.77 1 31 1 0
#> 45 17.42 1 54 0 1
#> 180 14.82 1 37 0 0
#> 96 14.54 1 33 0 1
#> 149 8.37 1 33 1 0
#> 171 16.57 1 41 0 1
#> 114 13.68 1 NA 0 0
#> 136 21.83 1 43 0 1
#> 107 11.18 1 54 1 0
#> 88 18.37 1 47 0 0
#> 18 15.21 1 49 1 0
#> 25 6.32 1 34 1 0
#> 40 18.00 1 28 1 0
#> 13 14.34 1 54 0 1
#> 195 11.76 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 181 16.46 1 45 0 1
#> 154 12.63 1 20 1 0
#> 134 17.81 1 47 1 0
#> 81 14.06 1 34 0 0
#> 13.1 14.34 1 54 0 1
#> 170 19.54 1 43 0 1
#> 197.1 21.60 1 69 1 0
#> 8 18.43 1 32 0 0
#> 117 17.46 1 26 0 1
#> 188 16.16 1 46 0 1
#> 55.1 19.34 1 69 0 1
#> 79 16.23 1 54 1 0
#> 89.2 11.44 1 NA 0 0
#> 153 21.33 1 55 1 0
#> 57 14.46 1 45 0 1
#> 63.2 22.77 1 31 1 0
#> 101.1 9.97 1 10 0 1
#> 166 19.98 1 48 0 0
#> 26 15.77 1 49 0 1
#> 127 3.53 1 62 0 1
#> 188.1 16.16 1 46 0 1
#> 79.1 16.23 1 54 1 0
#> 114.1 13.68 1 NA 0 0
#> 76.1 19.22 1 54 0 1
#> 24 23.89 1 38 0 0
#> 81.1 14.06 1 34 0 0
#> 123.2 13.00 1 44 1 0
#> 114.2 13.68 1 NA 0 0
#> 59 10.16 1 NA 1 0
#> 57.1 14.46 1 45 0 1
#> 139 21.49 1 63 1 0
#> 4 17.64 1 NA 0 1
#> 106 16.67 1 49 1 0
#> 88.1 18.37 1 47 0 0
#> 30 17.43 1 78 0 0
#> 4.1 17.64 1 NA 0 1
#> 189 10.51 1 NA 1 0
#> 197.2 21.60 1 69 1 0
#> 164 23.60 1 76 0 1
#> 36 21.19 1 48 0 1
#> 169 22.41 1 46 0 0
#> 145 10.07 1 65 1 0
#> 188.2 16.16 1 46 0 1
#> 127.1 3.53 1 62 0 1
#> 113 22.86 1 34 0 0
#> 159 10.55 1 50 0 1
#> 166.1 19.98 1 48 0 0
#> 140 12.68 1 59 1 0
#> 187 9.92 1 39 1 0
#> 169.1 22.41 1 46 0 0
#> 16 8.71 1 71 0 1
#> 113.1 22.86 1 34 0 0
#> 125.1 15.65 1 67 1 0
#> 157 15.10 1 47 0 0
#> 30.1 17.43 1 78 0 0
#> 6 15.64 1 39 0 0
#> 145.1 10.07 1 65 1 0
#> 164.1 23.60 1 76 0 1
#> 117.1 17.46 1 26 0 1
#> 61 10.12 1 36 0 1
#> 92 22.92 1 47 0 1
#> 153.1 21.33 1 55 1 0
#> 100 16.07 1 60 0 0
#> 188.3 16.16 1 46 0 1
#> 59.1 10.16 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 70 7.38 1 30 1 0
#> 105 19.75 1 60 0 0
#> 184 17.77 1 38 0 0
#> 181.1 16.46 1 45 0 1
#> 58 19.34 1 39 0 0
#> 189.1 10.51 1 NA 1 0
#> 55.2 19.34 1 69 0 1
#> 49 12.19 1 48 1 0
#> 42 12.43 1 49 0 1
#> 148 24.00 0 61 1 0
#> 64 24.00 0 43 0 0
#> 137 24.00 0 45 1 0
#> 3 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 109 24.00 0 48 0 0
#> 174 24.00 0 49 1 0
#> 120 24.00 0 68 0 1
#> 2 24.00 0 9 0 0
#> 156 24.00 0 50 1 0
#> 162 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 48 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 116 24.00 0 58 0 1
#> 20 24.00 0 46 1 0
#> 27 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 73 24.00 0 NA 0 1
#> 147 24.00 0 76 1 0
#> 146 24.00 0 63 1 0
#> 186 24.00 0 45 1 0
#> 82 24.00 0 34 0 0
#> 121.1 24.00 0 57 1 0
#> 65 24.00 0 57 1 0
#> 132 24.00 0 55 0 0
#> 182 24.00 0 35 0 0
#> 48.1 24.00 0 31 1 0
#> 162.1 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 196 24.00 0 19 0 0
#> 141 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 104.1 24.00 0 50 1 0
#> 174.1 24.00 0 49 1 0
#> 11.1 24.00 0 42 0 1
#> 185 24.00 0 44 1 0
#> 104.2 24.00 0 50 1 0
#> 112 24.00 0 61 0 0
#> 44 24.00 0 56 0 0
#> 200 24.00 0 64 0 0
#> 147.1 24.00 0 76 1 0
#> 28 24.00 0 67 1 0
#> 82.1 24.00 0 34 0 0
#> 33 24.00 0 53 0 0
#> 2.1 24.00 0 9 0 0
#> 115 24.00 0 NA 1 0
#> 172 24.00 0 41 0 0
#> 182.1 24.00 0 35 0 0
#> 163 24.00 0 66 0 0
#> 172.1 24.00 0 41 0 0
#> 147.2 24.00 0 76 1 0
#> 196.1 24.00 0 19 0 0
#> 151 24.00 0 42 0 0
#> 53 24.00 0 32 0 1
#> 7 24.00 0 37 1 0
#> 103 24.00 0 56 1 0
#> 165 24.00 0 47 0 0
#> 65.1 24.00 0 57 1 0
#> 19 24.00 0 57 0 1
#> 7.1 24.00 0 37 1 0
#> 71 24.00 0 51 0 0
#> 53.1 24.00 0 32 0 1
#> 74 24.00 0 43 0 1
#> 11.2 24.00 0 42 0 1
#> 156.1 24.00 0 50 1 0
#> 44.1 24.00 0 56 0 0
#> 182.2 24.00 0 35 0 0
#> 182.3 24.00 0 35 0 0
#> 9 24.00 0 31 1 0
#> 162.2 24.00 0 51 0 0
#> 112.1 24.00 0 61 0 0
#> 119 24.00 0 17 0 0
#> 186.1 24.00 0 45 1 0
#> 198 24.00 0 66 0 1
#> 191 24.00 0 60 0 1
#> 185.1 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 65.2 24.00 0 57 1 0
#> 98.1 24.00 0 34 1 0
#> 73.1 24.00 0 NA 0 1
#> 152 24.00 0 36 0 1
#> 64.1 24.00 0 43 0 0
#> 7.2 24.00 0 37 1 0
#> 34 24.00 0 36 0 0
#> 94 24.00 0 51 0 1
#> 94.1 24.00 0 51 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.693 NA NA NA
#> 2 age, Cure model 0.00963 NA NA NA
#> 3 grade_ii, Cure model 0.102 NA NA NA
#> 4 grade_iii, Cure model 1.27 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00900 NA NA NA
#> 2 grade_ii, Survival model 0.523 NA NA NA
#> 3 grade_iii, Survival model 0.567 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.693368 0.009626 0.102418 1.271254
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 254
#> Residual Deviance: 240 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.693367882 0.009625798 0.102417881 1.271254276
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008995778 0.523250133 0.567072598
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.837142346 0.919124195 0.247713360 0.306699582 0.110849714 0.348295510
#> [7] 0.059478684 0.969834473 0.197846754 0.743615225 0.286643463 0.743615225
#> [13] 0.888710308 0.494801634 0.659841424 0.130754263 0.847505794 0.083167009
#> [19] 0.617905400 0.059478684 0.442511892 0.649295366 0.670455537 0.939472496
#> [25] 0.463660375 0.120882627 0.816372402 0.327394947 0.628358954 0.959741436
#> [31] 0.358960892 0.701865465 0.586872794 0.474171521 0.785133891 0.369528417
#> [37] 0.722660884 0.701865465 0.237544311 0.130754263 0.317005010 0.390685100
#> [43] 0.526009642 0.247713360 0.505287634 0.168725700 0.681017778 0.059478684
#> [49] 0.888710308 0.207602050 0.576511894 0.979925569 0.526009642 0.505287634
#> [55] 0.286643463 0.003353253 0.722660884 0.743615225 0.681017778 0.158755413
#> [61] 0.453096733 0.327394947 0.421553478 0.130754263 0.013700955 0.188015693
#> [67] 0.092299188 0.868172000 0.526009642 0.979925569 0.040240729 0.826765489
#> [73] 0.207602050 0.774647463 0.908962486 0.092299188 0.929294495 0.040240729
#> [79] 0.586872794 0.638797585 0.421553478 0.607466802 0.868172000 0.013700955
#> [85] 0.390685100 0.857856032 0.030586878 0.168725700 0.566125877 0.526009642
#> [91] 0.411203550 0.949622560 0.227288623 0.380064129 0.474171521 0.247713360
#> [97] 0.247713360 0.805974262 0.795563261 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 52 183 55 179 66 51 63 91 190 123 76 123.1 101
#> 10.42 9.24 19.34 18.63 22.13 18.23 22.77 5.33 20.81 13.00 19.22 13.00 9.97
#> 85 133 197 93 15 29 63.1 45 180 96 149 171 136
#> 16.44 14.65 21.60 10.33 22.68 15.45 22.77 17.42 14.82 14.54 8.37 16.57 21.83
#> 107 88 18 25 40 13 125 181 154 134 81 13.1 170
#> 11.18 18.37 15.21 6.32 18.00 14.34 15.65 16.46 12.63 17.81 14.06 14.34 19.54
#> 197.1 8 117 188 55.1 79 153 57 63.2 101.1 166 26 127
#> 21.60 18.43 17.46 16.16 19.34 16.23 21.33 14.46 22.77 9.97 19.98 15.77 3.53
#> 188.1 79.1 76.1 24 81.1 123.2 57.1 139 106 88.1 30 197.2 164
#> 16.16 16.23 19.22 23.89 14.06 13.00 14.46 21.49 16.67 18.37 17.43 21.60 23.60
#> 36 169 145 188.2 127.1 113 159 166.1 140 187 169.1 16 113.1
#> 21.19 22.41 10.07 16.16 3.53 22.86 10.55 19.98 12.68 9.92 22.41 8.71 22.86
#> 125.1 157 30.1 6 145.1 164.1 117.1 61 92 153.1 100 188.3 111
#> 15.65 15.10 17.43 15.64 10.07 23.60 17.46 10.12 22.92 21.33 16.07 16.16 17.45
#> 70 105 184 181.1 58 55.2 49 42 148 64 137 3 104
#> 7.38 19.75 17.77 16.46 19.34 19.34 12.19 12.43 24.00 24.00 24.00 24.00 24.00
#> 109 174 120 2 156 162 121 48 87 116 20 27 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 146 186 82 121.1 65 132 182 48.1 162.1 122 196 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 104.1 174.1 11.1 185 104.2 112 44 200 147.1 28 82.1 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.1 172 182.1 163 172.1 147.2 196.1 151 53 7 103 165 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 7.1 71 53.1 74 11.2 156.1 44.1 182.2 182.3 9 162.2 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 186.1 198 191 185.1 35 38 65.2 98.1 152 64.1 7.2 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 94.1
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[53]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01124816 0.36001967 0.36022915
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.009723017 0.001138190 -0.211904008
#> grade_iii, Cure model
#> 0.653727791
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 123 13.00 1 44 1 0
#> 164 23.60 1 76 0 1
#> 13 14.34 1 54 0 1
#> 88 18.37 1 47 0 0
#> 79 16.23 1 54 1 0
#> 128 20.35 1 35 0 1
#> 29 15.45 1 68 1 0
#> 133 14.65 1 57 0 0
#> 92 22.92 1 47 0 1
#> 43 12.10 1 61 0 1
#> 179 18.63 1 42 0 0
#> 114 13.68 1 NA 0 0
#> 45 17.42 1 54 0 1
#> 76 19.22 1 54 0 1
#> 15 22.68 1 48 0 0
#> 52 10.42 1 52 0 1
#> 6 15.64 1 39 0 0
#> 55 19.34 1 69 0 1
#> 39 15.59 1 37 0 1
#> 155 13.08 1 26 0 0
#> 88.1 18.37 1 47 0 0
#> 79.1 16.23 1 54 1 0
#> 16 8.71 1 71 0 1
#> 77 7.27 1 67 0 1
#> 127 3.53 1 62 0 1
#> 61 10.12 1 36 0 1
#> 106 16.67 1 49 1 0
#> 187 9.92 1 39 1 0
#> 134 17.81 1 47 1 0
#> 91 5.33 1 61 0 1
#> 93 10.33 1 52 0 1
#> 24 23.89 1 38 0 0
#> 180 14.82 1 37 0 0
#> 5 16.43 1 51 0 1
#> 199 19.81 1 NA 0 1
#> 32 20.90 1 37 1 0
#> 117 17.46 1 26 0 1
#> 61.1 10.12 1 36 0 1
#> 124 9.73 1 NA 1 0
#> 79.2 16.23 1 54 1 0
#> 188 16.16 1 46 0 1
#> 68 20.62 1 44 0 0
#> 124.1 9.73 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 129 23.41 1 53 1 0
#> 107 11.18 1 54 1 0
#> 70 7.38 1 30 1 0
#> 37 12.52 1 57 1 0
#> 150 20.33 1 48 0 0
#> 133.1 14.65 1 57 0 0
#> 63 22.77 1 31 1 0
#> 179.1 18.63 1 42 0 0
#> 170 19.54 1 43 0 1
#> 130 16.47 1 53 0 1
#> 88.2 18.37 1 47 0 0
#> 195 11.76 1 NA 1 0
#> 91.1 5.33 1 61 0 1
#> 177.1 12.53 1 75 0 0
#> 29.1 15.45 1 68 1 0
#> 91.2 5.33 1 61 0 1
#> 81 14.06 1 34 0 0
#> 23 16.92 1 61 0 0
#> 86 23.81 1 58 0 1
#> 85 16.44 1 36 0 0
#> 99 21.19 1 38 0 1
#> 18 15.21 1 49 1 0
#> 169 22.41 1 46 0 0
#> 45.1 17.42 1 54 0 1
#> 25 6.32 1 34 1 0
#> 113 22.86 1 34 0 0
#> 149 8.37 1 33 1 0
#> 100 16.07 1 60 0 0
#> 8 18.43 1 32 0 0
#> 42 12.43 1 49 0 1
#> 29.2 15.45 1 68 1 0
#> 8.1 18.43 1 32 0 0
#> 93.1 10.33 1 52 0 1
#> 29.3 15.45 1 68 1 0
#> 90 20.94 1 50 0 1
#> 96 14.54 1 33 0 1
#> 149.1 8.37 1 33 1 0
#> 99.1 21.19 1 38 0 1
#> 110 17.56 1 65 0 1
#> 145 10.07 1 65 1 0
#> 180.1 14.82 1 37 0 0
#> 24.1 23.89 1 38 0 0
#> 197 21.60 1 69 1 0
#> 13.1 14.34 1 54 0 1
#> 26 15.77 1 49 0 1
#> 23.1 16.92 1 61 0 0
#> 117.1 17.46 1 26 0 1
#> 6.1 15.64 1 39 0 0
#> 167 15.55 1 56 1 0
#> 40 18.00 1 28 1 0
#> 188.1 16.16 1 46 0 1
#> 127.1 3.53 1 62 0 1
#> 32.1 20.90 1 37 1 0
#> 190 20.81 1 42 1 0
#> 49 12.19 1 48 1 0
#> 140 12.68 1 59 1 0
#> 59 10.16 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 85.1 16.44 1 36 0 0
#> 63.1 22.77 1 31 1 0
#> 85.2 16.44 1 36 0 0
#> 181 16.46 1 45 0 1
#> 24.2 23.89 1 38 0 0
#> 194 22.40 1 38 0 1
#> 61.2 10.12 1 36 0 1
#> 66 22.13 1 53 0 0
#> 56 12.21 1 60 0 0
#> 129.1 23.41 1 53 1 0
#> 147 24.00 0 76 1 0
#> 84 24.00 0 39 0 1
#> 161 24.00 0 45 0 0
#> 20 24.00 0 46 1 0
#> 151 24.00 0 42 0 0
#> 53 24.00 0 32 0 1
#> 103 24.00 0 56 1 0
#> 126 24.00 0 48 0 0
#> 28 24.00 0 67 1 0
#> 64 24.00 0 43 0 0
#> 120 24.00 0 68 0 1
#> 185 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 75 24.00 0 21 1 0
#> 138 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 193 24.00 0 45 0 1
#> 33 24.00 0 53 0 0
#> 46 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 22 24.00 0 52 1 0
#> 120.1 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 35 24.00 0 51 0 0
#> 119.1 24.00 0 17 0 0
#> 118 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 174 24.00 0 49 1 0
#> 44 24.00 0 56 0 0
#> 102 24.00 0 49 0 0
#> 84.1 24.00 0 39 0 1
#> 173 24.00 0 19 0 1
#> 144 24.00 0 28 0 1
#> 28.1 24.00 0 67 1 0
#> 62 24.00 0 71 0 0
#> 178 24.00 0 52 1 0
#> 173.1 24.00 0 19 0 1
#> 162 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 2 24.00 0 9 0 0
#> 94.1 24.00 0 51 0 1
#> 178.1 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 33.1 24.00 0 53 0 0
#> 118.1 24.00 0 44 1 0
#> 121.1 24.00 0 57 1 0
#> 161.1 24.00 0 45 0 0
#> 62.1 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 162.1 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 121.2 24.00 0 57 1 0
#> 121.3 24.00 0 57 1 0
#> 103.1 24.00 0 56 1 0
#> 47 24.00 0 38 0 1
#> 144.1 24.00 0 28 0 1
#> 87 24.00 0 27 0 0
#> 65 24.00 0 57 1 0
#> 82 24.00 0 34 0 0
#> 121.4 24.00 0 57 1 0
#> 156 24.00 0 50 1 0
#> 67 24.00 0 25 0 0
#> 141 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 12 24.00 0 63 0 0
#> 138.1 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 121.5 24.00 0 57 1 0
#> 176 24.00 0 43 0 1
#> 176.1 24.00 0 43 0 1
#> 74 24.00 0 43 0 1
#> 185.1 24.00 0 44 1 0
#> 28.2 24.00 0 67 1 0
#> 46.1 24.00 0 71 0 0
#> 191 24.00 0 60 0 1
#> 178.2 24.00 0 52 1 0
#> 7.1 24.00 0 37 1 0
#> 198 24.00 0 66 0 1
#> 186 24.00 0 45 1 0
#> 20.1 24.00 0 46 1 0
#> 147.1 24.00 0 76 1 0
#> 64.1 24.00 0 43 0 0
#> 112.1 24.00 0 61 0 0
#> 176.2 24.00 0 43 0 1
#> 151.1 24.00 0 42 0 0
#> 172 24.00 0 41 0 0
#> 31 24.00 0 36 0 1
#> 20.2 24.00 0 46 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.00972 NA NA NA
#> 2 age, Cure model 0.00114 NA NA NA
#> 3 grade_ii, Cure model -0.212 NA NA NA
#> 4 grade_iii, Cure model 0.654 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0112 NA NA NA
#> 2 grade_ii, Survival model 0.360 NA NA NA
#> 3 grade_iii, Survival model 0.360 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.009723 0.001138 -0.211904 0.653728
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 267.3
#> Residual Deviance: 261.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.009723017 0.001138190 -0.211904008 0.653727791
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01124816 0.36001967 0.36022915
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.8664901 0.2381018 0.8457165 0.5788486 0.7248387 0.4983739 0.7916463
#> [8] 0.8297221 0.2963460 0.9063718 0.5448743 0.6422722 0.5360892 0.3578672
#> [15] 0.9159552 0.7679575 0.5270627 0.7798696 0.8613041 0.5788486 0.7248387
#> [22] 0.9526861 0.9703585 0.9916890 0.9299782 0.6710990 0.9481784 0.6113751
#> [29] 0.9790500 0.9206876 0.1082574 0.8189212 0.7182599 0.4578541 0.6271430
#> [36] 0.9299782 0.7248387 0.7435720 0.4884281 0.8767253 0.2613741 0.9111841
#> [43] 0.9659617 0.8867239 0.5081012 0.8297221 0.3291249 0.5448743 0.5176970
#> [50] 0.6781539 0.5788486 0.9790500 0.8767253 0.7916463 0.9790500 0.8561075
#> [57] 0.6568415 0.2078246 0.6919369 0.4244575 0.8134656 0.3721209 0.6422722
#> [64] 0.9747149 0.3129352 0.9571477 0.7558235 0.5619726 0.8916891 0.7916463
#> [71] 0.5619726 0.9206876 0.7916463 0.4469069 0.8403980 0.9571477 0.4244575
#> [78] 0.6193583 0.9436443 0.8189212 0.1082574 0.4122995 0.8457165 0.7619264
#> [85] 0.6568415 0.6271430 0.7679575 0.7857953 0.6032397 0.7435720 0.9916890
#> [92] 0.4578541 0.4783510 0.9015119 0.8716345 0.6919369 0.6919369 0.3291249
#> [99] 0.6919369 0.6850932 0.1082574 0.3860141 0.9299782 0.3993330 0.8966135
#> [106] 0.2613741 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 123 164 13 88 79 128 29 133 92 43 179 45 76
#> 13.00 23.60 14.34 18.37 16.23 20.35 15.45 14.65 22.92 12.10 18.63 17.42 19.22
#> 15 52 6 55 39 155 88.1 79.1 16 77 127 61 106
#> 22.68 10.42 15.64 19.34 15.59 13.08 18.37 16.23 8.71 7.27 3.53 10.12 16.67
#> 187 134 91 93 24 180 5 32 117 61.1 79.2 188 68
#> 9.92 17.81 5.33 10.33 23.89 14.82 16.43 20.90 17.46 10.12 16.23 16.16 20.62
#> 177 129 107 70 37 150 133.1 63 179.1 170 130 88.2 91.1
#> 12.53 23.41 11.18 7.38 12.52 20.33 14.65 22.77 18.63 19.54 16.47 18.37 5.33
#> 177.1 29.1 91.2 81 23 86 85 99 18 169 45.1 25 113
#> 12.53 15.45 5.33 14.06 16.92 23.81 16.44 21.19 15.21 22.41 17.42 6.32 22.86
#> 149 100 8 42 29.2 8.1 93.1 29.3 90 96 149.1 99.1 110
#> 8.37 16.07 18.43 12.43 15.45 18.43 10.33 15.45 20.94 14.54 8.37 21.19 17.56
#> 145 180.1 24.1 197 13.1 26 23.1 117.1 6.1 167 40 188.1 127.1
#> 10.07 14.82 23.89 21.60 14.34 15.77 16.92 17.46 15.64 15.55 18.00 16.16 3.53
#> 32.1 190 49 140 192 85.1 63.1 85.2 181 24.2 194 61.2 66
#> 20.90 20.81 12.19 12.68 16.44 16.44 22.77 16.44 16.46 23.89 22.40 10.12 22.13
#> 56 129.1 147 84 161 20 151 53 103 126 28 64 120
#> 12.21 23.41 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 7 75 138 94 193 33 46 146 22 120.1 119 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 118 121 174 44 102 84.1 173 144 28.1 62 178 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 112 2 94.1 178.1 71 33.1 118.1 121.1 161.1 62.1 200 162.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 121.2 121.3 103.1 47 144.1 87 65 82 121.4 156 67 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 12 138.1 48 121.5 176 176.1 74 185.1 28.2 46.1 191 178.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.1 198 186 20.1 147.1 64.1 112.1 176.2 151.1 172 31 20.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[54]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006731615 0.487219917 0.426633520
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.246542468 0.006423683 -0.147063416
#> grade_iii, Cure model
#> 0.399003805
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 168 23.72 1 70 0 0
#> 13 14.34 1 54 0 1
#> 177 12.53 1 75 0 0
#> 56 12.21 1 60 0 0
#> 130 16.47 1 53 0 1
#> 66 22.13 1 53 0 0
#> 113 22.86 1 34 0 0
#> 68 20.62 1 44 0 0
#> 130.1 16.47 1 53 0 1
#> 124 9.73 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 63 22.77 1 31 1 0
#> 10 10.53 1 34 0 0
#> 77 7.27 1 67 0 1
#> 58 19.34 1 39 0 0
#> 134 17.81 1 47 1 0
#> 24 23.89 1 38 0 0
#> 158 20.14 1 74 1 0
#> 123 13.00 1 44 1 0
#> 159 10.55 1 50 0 1
#> 25 6.32 1 34 1 0
#> 93 10.33 1 52 0 1
#> 113.1 22.86 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 49 12.19 1 48 1 0
#> 159.1 10.55 1 50 0 1
#> 40 18.00 1 28 1 0
#> 92 22.92 1 47 0 1
#> 179 18.63 1 42 0 0
#> 107 11.18 1 54 1 0
#> 89 11.44 1 NA 0 0
#> 199 19.81 1 NA 0 1
#> 66.1 22.13 1 53 0 0
#> 10.1 10.53 1 34 0 0
#> 180 14.82 1 37 0 0
#> 133 14.65 1 57 0 0
#> 69 23.23 1 25 0 1
#> 110 17.56 1 65 0 1
#> 29 15.45 1 68 1 0
#> 76 19.22 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 155 13.08 1 26 0 0
#> 199.1 19.81 1 NA 0 1
#> 14 12.89 1 21 0 0
#> 43 12.10 1 61 0 1
#> 175 21.91 1 43 0 0
#> 8 18.43 1 32 0 0
#> 92.1 22.92 1 47 0 1
#> 88 18.37 1 47 0 0
#> 59 10.16 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 117 17.46 1 26 0 1
#> 45 17.42 1 54 0 1
#> 32 20.90 1 37 1 0
#> 66.2 22.13 1 53 0 0
#> 181 16.46 1 45 0 1
#> 69.1 23.23 1 25 0 1
#> 105 19.75 1 60 0 0
#> 42 12.43 1 49 0 1
#> 52 10.42 1 52 0 1
#> 59.1 10.16 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 114 13.68 1 NA 0 0
#> 91 5.33 1 61 0 1
#> 86 23.81 1 58 0 1
#> 111 17.45 1 47 0 1
#> 42.1 12.43 1 49 0 1
#> 101 9.97 1 10 0 1
#> 127 3.53 1 62 0 1
#> 42.2 12.43 1 49 0 1
#> 58.1 19.34 1 39 0 0
#> 85 16.44 1 36 0 0
#> 145 10.07 1 65 1 0
#> 175.1 21.91 1 43 0 0
#> 10.2 10.53 1 34 0 0
#> 168.1 23.72 1 70 0 0
#> 32.1 20.90 1 37 1 0
#> 32.2 20.90 1 37 1 0
#> 107.1 11.18 1 54 1 0
#> 192 16.44 1 31 1 0
#> 45.1 17.42 1 54 0 1
#> 130.2 16.47 1 53 0 1
#> 164 23.60 1 76 0 1
#> 96 14.54 1 33 0 1
#> 18 15.21 1 49 1 0
#> 70 7.38 1 30 1 0
#> 183 9.24 1 67 1 0
#> 50 10.02 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 4.1 17.64 1 NA 0 1
#> 154 12.63 1 20 1 0
#> 139 21.49 1 63 1 0
#> 190 20.81 1 42 1 0
#> 30 17.43 1 78 0 0
#> 61 10.12 1 36 0 1
#> 127.1 3.53 1 62 0 1
#> 168.2 23.72 1 70 0 0
#> 55 19.34 1 69 0 1
#> 129 23.41 1 53 1 0
#> 188 16.16 1 46 0 1
#> 58.2 19.34 1 39 0 0
#> 58.3 19.34 1 39 0 0
#> 18.1 15.21 1 49 1 0
#> 133.1 14.65 1 57 0 0
#> 114.1 13.68 1 NA 0 0
#> 57 14.46 1 45 0 1
#> 197 21.60 1 69 1 0
#> 107.2 11.18 1 54 1 0
#> 155.1 13.08 1 26 0 0
#> 6.1 15.64 1 39 0 0
#> 171 16.57 1 41 0 1
#> 19 24.00 0 57 0 1
#> 75 24.00 0 21 1 0
#> 44 24.00 0 56 0 0
#> 102 24.00 0 49 0 0
#> 174 24.00 0 49 1 0
#> 160 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 21 24.00 0 47 0 0
#> 141 24.00 0 44 1 0
#> 21.1 24.00 0 47 0 0
#> 3 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 9 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 176 24.00 0 43 0 1
#> 160.1 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 144 24.00 0 28 0 1
#> 19.1 24.00 0 57 0 1
#> 104 24.00 0 50 1 0
#> 34 24.00 0 36 0 0
#> 75.1 24.00 0 21 1 0
#> 12 24.00 0 63 0 0
#> 138 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 48 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 112.1 24.00 0 61 0 0
#> 162 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 19.2 24.00 0 57 0 1
#> 38 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 87 24.00 0 27 0 0
#> 119 24.00 0 17 0 0
#> 122 24.00 0 66 0 0
#> 74.1 24.00 0 43 0 1
#> 103 24.00 0 56 1 0
#> 165 24.00 0 47 0 0
#> 112.2 24.00 0 61 0 0
#> 21.2 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 33 24.00 0 53 0 0
#> 191 24.00 0 60 0 1
#> 95 24.00 0 68 0 1
#> 104.1 24.00 0 50 1 0
#> 173 24.00 0 19 0 1
#> 62 24.00 0 71 0 0
#> 28 24.00 0 67 1 0
#> 165.1 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 191.1 24.00 0 60 0 1
#> 118 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 17 24.00 0 38 0 1
#> 144.1 24.00 0 28 0 1
#> 44.1 24.00 0 56 0 0
#> 71 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 71.1 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 174.1 24.00 0 49 1 0
#> 22 24.00 0 52 1 0
#> 48.1 24.00 0 31 1 0
#> 87.1 24.00 0 27 0 0
#> 152.1 24.00 0 36 0 1
#> 146 24.00 0 63 1 0
#> 46 24.00 0 71 0 0
#> 71.2 24.00 0 51 0 0
#> 12.1 24.00 0 63 0 0
#> 1 24.00 0 23 1 0
#> 147 24.00 0 76 1 0
#> 141.1 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 116.1 24.00 0 58 0 1
#> 17.1 24.00 0 38 0 1
#> 174.2 24.00 0 49 1 0
#> 118.1 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 3.1 24.00 0 31 1 0
#> 19.3 24.00 0 57 0 1
#> 20 24.00 0 46 1 0
#> 54 24.00 0 53 1 0
#> 47 24.00 0 38 0 1
#> 122.1 24.00 0 66 0 0
#> 22.1 24.00 0 52 1 0
#> 80 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.247 NA NA NA
#> 2 age, Cure model 0.00642 NA NA NA
#> 3 grade_ii, Cure model -0.147 NA NA NA
#> 4 grade_iii, Cure model 0.399 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00673 NA NA NA
#> 2 grade_ii, Survival model 0.487 NA NA NA
#> 3 grade_iii, Survival model 0.427 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.246542 0.006424 -0.147063 0.399004
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 255.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.246542468 0.006423683 -0.147063416 0.399003805
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006731615 0.487219917 0.426633520
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.020734922 0.658272591 0.729256074 0.769391816 0.466359775 0.135061004
#> [7] 0.106376640 0.253787445 0.466359775 0.557015932 0.125401841 0.849730619
#> [13] 0.950238769 0.283731900 0.384127252 0.003281138 0.263725682 0.698814197
#> [19] 0.829728734 0.960237495 0.889892693 0.106376640 0.779557638 0.829728734
#> [25] 0.373726795 0.088029476 0.342443034 0.799840013 0.135061004 0.849730619
#> [31] 0.607397596 0.617540973 0.069242449 0.394475531 0.577184714 0.332158558
#> [37] 0.526667934 0.678591069 0.708968842 0.789699875 0.163747732 0.352804161
#> [43] 0.088029476 0.363224612 0.204980103 0.404826776 0.435697781 0.215353521
#> [49] 0.135061004 0.496365836 0.069242449 0.273668032 0.739425357 0.879771986
#> [55] 0.668451930 0.970205626 0.011937523 0.415102865 0.739425357 0.920175793
#> [61] 0.980172105 0.739425357 0.283731900 0.506548880 0.910092865 0.163747732
#> [67] 0.849730619 0.020734922 0.215353521 0.215353521 0.799840013 0.506548880
#> [73] 0.435697781 0.466359775 0.046813673 0.637872247 0.587353419 0.940242577
#> [79] 0.930211179 0.536808424 0.719142698 0.194557103 0.243948019 0.425349404
#> [85] 0.900004247 0.980172105 0.020734922 0.283731900 0.058174767 0.546923757
#> [91] 0.283731900 0.283731900 0.587353419 0.617540973 0.648082988 0.184097734
#> [97] 0.799840013 0.678591069 0.557015932 0.456086573 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 168 13 177 56 130 66 113 68 130.1 6 63 10 77
#> 23.72 14.34 12.53 12.21 16.47 22.13 22.86 20.62 16.47 15.64 22.77 10.53 7.27
#> 58 134 24 158 123 159 25 93 113.1 49 159.1 40 92
#> 19.34 17.81 23.89 20.14 13.00 10.55 6.32 10.33 22.86 12.19 10.55 18.00 22.92
#> 179 107 66.1 10.1 180 133 69 110 29 76 5 155 14
#> 18.63 11.18 22.13 10.53 14.82 14.65 23.23 17.56 15.45 19.22 16.43 13.08 12.89
#> 43 175 8 92.1 88 90 117 45 32 66.2 181 69.1 105
#> 12.10 21.91 18.43 22.92 18.37 20.94 17.46 17.42 20.90 22.13 16.46 23.23 19.75
#> 42 52 60 91 86 111 42.1 101 127 42.2 58.1 85 145
#> 12.43 10.42 13.15 5.33 23.81 17.45 12.43 9.97 3.53 12.43 19.34 16.44 10.07
#> 175.1 10.2 168.1 32.1 32.2 107.1 192 45.1 130.2 164 96 18 70
#> 21.91 10.53 23.72 20.90 20.90 11.18 16.44 17.42 16.47 23.60 14.54 15.21 7.38
#> 183 79 154 139 190 30 61 127.1 168.2 55 129 188 58.2
#> 9.24 16.23 12.63 21.49 20.81 17.43 10.12 3.53 23.72 19.34 23.41 16.16 19.34
#> 58.3 18.1 133.1 57 197 107.2 155.1 6.1 171 19 75 44 102
#> 19.34 15.21 14.65 14.46 21.60 11.18 13.08 15.64 16.57 24.00 24.00 24.00 24.00
#> 174 160 21 141 21.1 3 116 9 53 176 160.1 112 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 104 34 75.1 12 138 193 48 72 112.1 162 74 19.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 161 87 119 122 74.1 103 165 112.2 21.2 94 33 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 104.1 173 62 28 165.1 131 191.1 118 83 17 144.1 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 152 132 71.1 126 174.1 22 48.1 87.1 152.1 146 46 71.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.1 1 147 141.1 98 116.1 17.1 174.2 118.1 182 3.1 19.3 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 47 122.1 22.1 80
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[55]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0001778183 0.2632714919 0.1204453297
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.189128803 -0.009174734 0.081248820
#> grade_iii, Cure model
#> 1.162918244
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 171 16.57 1 41 0 1
#> 124 9.73 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 105 19.75 1 60 0 0
#> 8 18.43 1 32 0 0
#> 133 14.65 1 57 0 0
#> 4 17.64 1 NA 0 1
#> 55 19.34 1 69 0 1
#> 8.1 18.43 1 32 0 0
#> 128 20.35 1 35 0 1
#> 187 9.92 1 39 1 0
#> 150 20.33 1 48 0 0
#> 171.1 16.57 1 41 0 1
#> 24 23.89 1 38 0 0
#> 133.1 14.65 1 57 0 0
#> 136 21.83 1 43 0 1
#> 76 19.22 1 54 0 1
#> 157 15.10 1 47 0 0
#> 113 22.86 1 34 0 0
#> 180 14.82 1 37 0 0
#> 40 18.00 1 28 1 0
#> 90 20.94 1 50 0 1
#> 93 10.33 1 52 0 1
#> 194 22.40 1 38 0 1
#> 68 20.62 1 44 0 0
#> 177 12.53 1 75 0 0
#> 32 20.90 1 37 1 0
#> 180.1 14.82 1 37 0 0
#> 52 10.42 1 52 0 1
#> 70 7.38 1 30 1 0
#> 23 16.92 1 61 0 0
#> 85 16.44 1 36 0 0
#> 197 21.60 1 69 1 0
#> 97 19.14 1 65 0 1
#> 4.1 17.64 1 NA 0 1
#> 52.1 10.42 1 52 0 1
#> 192 16.44 1 31 1 0
#> 114 13.68 1 NA 0 0
#> 13 14.34 1 54 0 1
#> 150.1 20.33 1 48 0 0
#> 158 20.14 1 74 1 0
#> 69 23.23 1 25 0 1
#> 57 14.46 1 45 0 1
#> 199 19.81 1 NA 0 1
#> 45 17.42 1 54 0 1
#> 39 15.59 1 37 0 1
#> 50 10.02 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 76.1 19.22 1 54 0 1
#> 123 13.00 1 44 1 0
#> 100.1 16.07 1 60 0 0
#> 188 16.16 1 46 0 1
#> 36 21.19 1 48 0 1
#> 97.1 19.14 1 65 0 1
#> 194.1 22.40 1 38 0 1
#> 106 16.67 1 49 1 0
#> 154 12.63 1 20 1 0
#> 8.2 18.43 1 32 0 0
#> 136.1 21.83 1 43 0 1
#> 106.1 16.67 1 49 1 0
#> 168 23.72 1 70 0 0
#> 14 12.89 1 21 0 0
#> 159 10.55 1 50 0 1
#> 8.3 18.43 1 32 0 0
#> 6 15.64 1 39 0 0
#> 16 8.71 1 71 0 1
#> 127 3.53 1 62 0 1
#> 197.1 21.60 1 69 1 0
#> 149 8.37 1 33 1 0
#> 76.2 19.22 1 54 0 1
#> 128.1 20.35 1 35 0 1
#> 85.1 16.44 1 36 0 0
#> 189 10.51 1 NA 1 0
#> 69.1 23.23 1 25 0 1
#> 42 12.43 1 49 0 1
#> 15 22.68 1 48 0 0
#> 41 18.02 1 40 1 0
#> 130 16.47 1 53 0 1
#> 129 23.41 1 53 1 0
#> 10 10.53 1 34 0 0
#> 90.1 20.94 1 50 0 1
#> 110 17.56 1 65 0 1
#> 37 12.52 1 57 1 0
#> 25 6.32 1 34 1 0
#> 106.2 16.67 1 49 1 0
#> 49 12.19 1 48 1 0
#> 37.1 12.52 1 57 1 0
#> 101 9.97 1 10 0 1
#> 89 11.44 1 NA 0 0
#> 6.1 15.64 1 39 0 0
#> 90.2 20.94 1 50 0 1
#> 179 18.63 1 42 0 0
#> 26 15.77 1 49 0 1
#> 40.1 18.00 1 28 1 0
#> 42.1 12.43 1 49 0 1
#> 108 18.29 1 39 0 1
#> 16.1 8.71 1 71 0 1
#> 36.1 21.19 1 48 0 1
#> 43 12.10 1 61 0 1
#> 70.1 7.38 1 30 1 0
#> 5 16.43 1 51 0 1
#> 130.1 16.47 1 53 0 1
#> 88 18.37 1 47 0 0
#> 40.2 18.00 1 28 1 0
#> 16.2 8.71 1 71 0 1
#> 50.1 10.02 1 NA 1 0
#> 187.1 9.92 1 39 1 0
#> 194.2 22.40 1 38 0 1
#> 129.1 23.41 1 53 1 0
#> 166 19.98 1 48 0 0
#> 170 19.54 1 43 0 1
#> 159.1 10.55 1 50 0 1
#> 46 24.00 0 71 0 0
#> 74 24.00 0 43 0 1
#> 162 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 67 24.00 0 25 0 0
#> 65 24.00 0 57 1 0
#> 54 24.00 0 53 1 0
#> 160 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 47 24.00 0 38 0 1
#> 87 24.00 0 27 0 0
#> 103 24.00 0 56 1 0
#> 38 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 178 24.00 0 52 1 0
#> 34 24.00 0 36 0 0
#> 103.1 24.00 0 56 1 0
#> 28 24.00 0 67 1 0
#> 103.2 24.00 0 56 1 0
#> 64 24.00 0 43 0 0
#> 120 24.00 0 68 0 1
#> 98 24.00 0 34 1 0
#> 84 24.00 0 39 0 1
#> 54.1 24.00 0 53 1 0
#> 80 24.00 0 41 0 0
#> 54.2 24.00 0 53 1 0
#> 20 24.00 0 46 1 0
#> 22 24.00 0 52 1 0
#> 126.1 24.00 0 48 0 0
#> 174 24.00 0 49 1 0
#> 131 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 191 24.00 0 60 0 1
#> 193 24.00 0 45 0 1
#> 62 24.00 0 71 0 0
#> 172 24.00 0 41 0 0
#> 33.1 24.00 0 53 0 0
#> 83 24.00 0 6 0 0
#> 62.1 24.00 0 71 0 0
#> 46.1 24.00 0 71 0 0
#> 1 24.00 0 23 1 0
#> 21 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 34.1 24.00 0 36 0 0
#> 122 24.00 0 66 0 0
#> 46.2 24.00 0 71 0 0
#> 87.1 24.00 0 27 0 0
#> 141 24.00 0 44 1 0
#> 33.2 24.00 0 53 0 0
#> 131.1 24.00 0 66 0 0
#> 72 24.00 0 40 0 1
#> 103.3 24.00 0 56 1 0
#> 115 24.00 0 NA 1 0
#> 20.1 24.00 0 46 1 0
#> 116 24.00 0 58 0 1
#> 109.1 24.00 0 48 0 0
#> 165.1 24.00 0 47 0 0
#> 178.1 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 94.1 24.00 0 51 0 1
#> 142 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 44 24.00 0 56 0 0
#> 2 24.00 0 9 0 0
#> 143 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 84.1 24.00 0 39 0 1
#> 62.2 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 2.1 24.00 0 9 0 0
#> 160.1 24.00 0 31 1 0
#> 84.2 24.00 0 39 0 1
#> 84.3 24.00 0 39 0 1
#> 48.1 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 44.1 24.00 0 56 0 0
#> 115.1 24.00 0 NA 1 0
#> 84.4 24.00 0 39 0 1
#> 87.2 24.00 0 27 0 0
#> 191.1 24.00 0 60 0 1
#> 142.1 24.00 0 53 0 0
#> 74.1 24.00 0 43 0 1
#> 126.2 24.00 0 48 0 0
#> 84.5 24.00 0 39 0 1
#> 148 24.00 0 61 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.189 NA NA NA
#> 2 age, Cure model -0.00917 NA NA NA
#> 3 grade_ii, Cure model 0.0812 NA NA NA
#> 4 grade_iii, Cure model 1.16 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000178 NA NA NA
#> 2 grade_ii, Survival model 0.263 NA NA NA
#> 3 grade_iii, Survival model 0.120 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.189129 -0.009175 0.081249 1.162918
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 246.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.189128803 -0.009174734 0.081248820 1.162918244
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0001778183 0.2632714919 0.1204453297
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.56516400 0.64688389 0.32656267 0.41468609 0.72811834 0.34669446
#> [7] 0.41468609 0.26625028 0.91416309 0.28632108 0.56516400 0.01025281
#> [13] 0.72811834 0.15101252 0.35669869 0.70108149 0.09330034 0.71013323
#> [19] 0.48160310 0.21545523 0.89666976 0.11840741 0.25591135 0.79105850
#> [25] 0.24556920 0.71013323 0.87922740 0.96581057 0.52839067 0.60168526
#> [31] 0.17317127 0.38555117 0.87922740 0.60168526 0.75512907 0.28632108
#> [37] 0.30638041 0.06985955 0.74609894 0.51896200 0.69202878 0.35669869
#> [43] 0.76414423 0.64688389 0.63779024 0.19447016 0.38555117 0.11840741
#> [49] 0.53781751 0.78210816 0.41468609 0.15101252 0.53781751 0.02768297
#> [55] 0.77312639 0.85294772 0.41468609 0.67401006 0.93145974 0.99145323
#> [61] 0.17317127 0.95718245 0.35669869 0.26625028 0.60168526 0.06985955
#> [67] 0.81768172 0.10585937 0.47193974 0.58346423 0.04542385 0.87043828
#> [73] 0.21545523 0.50950948 0.80000748 0.98289610 0.53781751 0.83530346
#> [79] 0.80000748 0.90542191 0.67401006 0.21545523 0.40489670 0.66493799
#> [85] 0.48160310 0.81768172 0.46221456 0.93145974 0.19447016 0.84413206
#> [91] 0.96581057 0.62867876 0.58346423 0.45246150 0.48160310 0.93145974
#> [97] 0.91416309 0.11840741 0.04542385 0.31647291 0.33664912 0.85294772
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 171 100 105 8 133 55 8.1 128 187 150 171.1 24 133.1
#> 16.57 16.07 19.75 18.43 14.65 19.34 18.43 20.35 9.92 20.33 16.57 23.89 14.65
#> 136 76 157 113 180 40 90 93 194 68 177 32 180.1
#> 21.83 19.22 15.10 22.86 14.82 18.00 20.94 10.33 22.40 20.62 12.53 20.90 14.82
#> 52 70 23 85 197 97 52.1 192 13 150.1 158 69 57
#> 10.42 7.38 16.92 16.44 21.60 19.14 10.42 16.44 14.34 20.33 20.14 23.23 14.46
#> 45 39 76.1 123 100.1 188 36 97.1 194.1 106 154 8.2 136.1
#> 17.42 15.59 19.22 13.00 16.07 16.16 21.19 19.14 22.40 16.67 12.63 18.43 21.83
#> 106.1 168 14 159 8.3 6 16 127 197.1 149 76.2 128.1 85.1
#> 16.67 23.72 12.89 10.55 18.43 15.64 8.71 3.53 21.60 8.37 19.22 20.35 16.44
#> 69.1 42 15 41 130 129 10 90.1 110 37 25 106.2 49
#> 23.23 12.43 22.68 18.02 16.47 23.41 10.53 20.94 17.56 12.52 6.32 16.67 12.19
#> 37.1 101 6.1 90.2 179 26 40.1 42.1 108 16.1 36.1 43 70.1
#> 12.52 9.97 15.64 20.94 18.63 15.77 18.00 12.43 18.29 8.71 21.19 12.10 7.38
#> 5 130.1 88 40.2 16.2 187.1 194.2 129.1 166 170 159.1 46 74
#> 16.43 16.47 18.37 18.00 8.71 9.92 22.40 23.41 19.98 19.54 10.55 24.00 24.00
#> 162 165 126 67 65 54 160 7 47 87 103 38 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 34 103.1 28 103.2 64 120 98 84 54.1 80 54.2 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 126.1 174 131 118 33 191 193 62 172 33.1 83 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1 1 21 48 135 34.1 122 46.2 87.1 141 33.2 131.1 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.3 20.1 116 109.1 165.1 178.1 94 94.1 142 95 44 2 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 84.1 62.2 146 2.1 160.1 84.2 84.3 48.1 121 44.1 84.4 87.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 142.1 74.1 126.2 84.5 148
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[56]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005894805 0.146777249 -0.028658685
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.106845902 -0.002298364 0.195115426
#> grade_iii, Cure model
#> 0.755351344
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 16 8.71 1 71 0 1
#> 105 19.75 1 60 0 0
#> 101 9.97 1 10 0 1
#> 153 21.33 1 55 1 0
#> 175 21.91 1 43 0 0
#> 129 23.41 1 53 1 0
#> 125 15.65 1 67 1 0
#> 23 16.92 1 61 0 0
#> 171 16.57 1 41 0 1
#> 127 3.53 1 62 0 1
#> 166 19.98 1 48 0 0
#> 77 7.27 1 67 0 1
#> 113 22.86 1 34 0 0
#> 139 21.49 1 63 1 0
#> 155 13.08 1 26 0 0
#> 32 20.90 1 37 1 0
#> 18 15.21 1 49 1 0
#> 166.1 19.98 1 48 0 0
#> 30 17.43 1 78 0 0
#> 61 10.12 1 36 0 1
#> 136 21.83 1 43 0 1
#> 58 19.34 1 39 0 0
#> 167 15.55 1 56 1 0
#> 97 19.14 1 65 0 1
#> 29 15.45 1 68 1 0
#> 157 15.10 1 47 0 0
#> 117 17.46 1 26 0 1
#> 133 14.65 1 57 0 0
#> 154 12.63 1 20 1 0
#> 14 12.89 1 21 0 0
#> 92 22.92 1 47 0 1
#> 57 14.46 1 45 0 1
#> 88 18.37 1 47 0 0
#> 23.1 16.92 1 61 0 0
#> 153.1 21.33 1 55 1 0
#> 61.1 10.12 1 36 0 1
#> 10 10.53 1 34 0 0
#> 97.1 19.14 1 65 0 1
#> 128 20.35 1 35 0 1
#> 39 15.59 1 37 0 1
#> 10.1 10.53 1 34 0 0
#> 49 12.19 1 48 1 0
#> 43 12.10 1 61 0 1
#> 136.1 21.83 1 43 0 1
#> 79 16.23 1 54 1 0
#> 29.1 15.45 1 68 1 0
#> 41 18.02 1 40 1 0
#> 70 7.38 1 30 1 0
#> 88.1 18.37 1 47 0 0
#> 78 23.88 1 43 0 0
#> 15 22.68 1 48 0 0
#> 184 17.77 1 38 0 0
#> 69 23.23 1 25 0 1
#> 36 21.19 1 48 0 1
#> 179 18.63 1 42 0 0
#> 164 23.60 1 76 0 1
#> 180 14.82 1 37 0 0
#> 190 20.81 1 42 1 0
#> 134 17.81 1 47 1 0
#> 177 12.53 1 75 0 0
#> 56 12.21 1 60 0 0
#> 93 10.33 1 52 0 1
#> 139.1 21.49 1 63 1 0
#> 10.2 10.53 1 34 0 0
#> 85 16.44 1 36 0 0
#> 123 13.00 1 44 1 0
#> 155.1 13.08 1 26 0 0
#> 170 19.54 1 43 0 1
#> 60 13.15 1 38 1 0
#> 153.2 21.33 1 55 1 0
#> 155.2 13.08 1 26 0 0
#> 32.1 20.90 1 37 1 0
#> 76 19.22 1 54 0 1
#> 49.1 12.19 1 48 1 0
#> 97.2 19.14 1 65 0 1
#> 18.1 15.21 1 49 1 0
#> 175.1 21.91 1 43 0 0
#> 101.1 9.97 1 10 0 1
#> 26 15.77 1 49 0 1
#> 114 13.68 1 NA 0 0
#> 42 12.43 1 49 0 1
#> 90 20.94 1 50 0 1
#> 110 17.56 1 65 0 1
#> 79.1 16.23 1 54 1 0
#> 81 14.06 1 34 0 0
#> 133.1 14.65 1 57 0 0
#> 30.1 17.43 1 78 0 0
#> 60.1 13.15 1 38 1 0
#> 70.1 7.38 1 30 1 0
#> 6 15.64 1 39 0 0
#> 166.2 19.98 1 48 0 0
#> 88.2 18.37 1 47 0 0
#> 192 16.44 1 31 1 0
#> 56.1 12.21 1 60 0 0
#> 92.1 22.92 1 47 0 1
#> 18.2 15.21 1 49 1 0
#> 93.1 10.33 1 52 0 1
#> 41.1 18.02 1 40 1 0
#> 179.1 18.63 1 42 0 0
#> 16.1 8.71 1 71 0 1
#> 42.1 12.43 1 49 0 1
#> 188 16.16 1 46 0 1
#> 171.1 16.57 1 41 0 1
#> 56.2 12.21 1 60 0 0
#> 183 9.24 1 67 1 0
#> 125.1 15.65 1 67 1 0
#> 79.2 16.23 1 54 1 0
#> 81.1 14.06 1 34 0 0
#> 59 10.16 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 37 12.52 1 57 1 0
#> 55 19.34 1 69 0 1
#> 141 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 186 24.00 0 45 1 0
#> 87 24.00 0 27 0 0
#> 115 24.00 0 NA 1 0
#> 73 24.00 0 NA 0 1
#> 53 24.00 0 32 0 1
#> 109 24.00 0 48 0 0
#> 65 24.00 0 57 1 0
#> 131 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 143 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 120 24.00 0 68 0 1
#> 44 24.00 0 56 0 0
#> 7 24.00 0 37 1 0
#> 33 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 34 24.00 0 36 0 0
#> 120.1 24.00 0 68 0 1
#> 116 24.00 0 58 0 1
#> 65.1 24.00 0 57 1 0
#> 54 24.00 0 53 1 0
#> 174 24.00 0 49 1 0
#> 64 24.00 0 43 0 0
#> 1 24.00 0 23 1 0
#> 33.1 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 28 24.00 0 67 1 0
#> 126 24.00 0 48 0 0
#> 182 24.00 0 35 0 0
#> 126.1 24.00 0 48 0 0
#> 163 24.00 0 66 0 0
#> 119 24.00 0 17 0 0
#> 47 24.00 0 38 0 1
#> 141.1 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 83 24.00 0 6 0 0
#> 116.1 24.00 0 58 0 1
#> 112 24.00 0 61 0 0
#> 83.1 24.00 0 6 0 0
#> 33.2 24.00 0 53 0 0
#> 72 24.00 0 40 0 1
#> 120.2 24.00 0 68 0 1
#> 200.1 24.00 0 64 0 0
#> 185 24.00 0 44 1 0
#> 131.1 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 138 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 200.2 24.00 0 64 0 0
#> 156 24.00 0 50 1 0
#> 74 24.00 0 43 0 1
#> 54.1 24.00 0 53 1 0
#> 64.1 24.00 0 43 0 0
#> 33.3 24.00 0 53 0 0
#> 33.4 24.00 0 53 0 0
#> 104 24.00 0 50 1 0
#> 12 24.00 0 63 0 0
#> 152 24.00 0 36 0 1
#> 176 24.00 0 43 0 1
#> 119.1 24.00 0 17 0 0
#> 48 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 141.2 24.00 0 44 1 0
#> 74.1 24.00 0 43 0 1
#> 54.2 24.00 0 53 1 0
#> 198 24.00 0 66 0 1
#> 44.1 24.00 0 56 0 0
#> 131.2 24.00 0 66 0 0
#> 186.1 24.00 0 45 1 0
#> 121 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 21 24.00 0 47 0 0
#> 115.1 24.00 0 NA 1 0
#> 135 24.00 0 58 1 0
#> 143.1 24.00 0 51 0 0
#> 182.1 24.00 0 35 0 0
#> 11 24.00 0 42 0 1
#> 186.2 24.00 0 45 1 0
#> 147 24.00 0 76 1 0
#> 27 24.00 0 63 1 0
#> 112.1 24.00 0 61 0 0
#> 198.1 24.00 0 66 0 1
#> 80 24.00 0 41 0 0
#> 196 24.00 0 19 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.107 NA NA NA
#> 2 age, Cure model -0.00230 NA NA NA
#> 3 grade_ii, Cure model 0.195 NA NA NA
#> 4 grade_iii, Cure model 0.755 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00589 NA NA NA
#> 2 grade_ii, Survival model 0.147 NA NA NA
#> 3 grade_iii, Survival model -0.0287 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.106846 -0.002298 0.195115 0.755351
#>
#> Degrees of Freedom: 194 Total (i.e. Null); 191 Residual
#> Null Deviance: 267.1
#> Residual Deviance: 262.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.106845902 -0.002298364 0.195115426 0.755351344
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005894805 0.146777249 -0.028658685
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.931778801 0.162710093 0.898106529 0.077436449 0.039883592 0.008396340
#> [7] 0.446211173 0.341718088 0.360355509 0.988516054 0.140631298 0.977075403
#> [13] 0.028126585 0.064330649 0.638946716 0.111507908 0.515829950 0.140631298
#> [19] 0.323382872 0.875771211 0.051747403 0.178461219 0.485760715 0.202542233
#> [25] 0.495791385 0.545823590 0.314274746 0.566326701 0.702013940 0.680762315
#> [31] 0.018133146 0.586891594 0.244140736 0.341718088 0.077436449 0.875771211
#> [37] 0.820695891 0.202542233 0.133157268 0.475764627 0.820695891 0.787874757
#> [43] 0.809673890 0.051747403 0.398200146 0.495791385 0.269817639 0.954419130
#> [49] 0.244140736 0.001131397 0.033878488 0.296235899 0.013109935 0.097032624
#> [55] 0.227149670 0.004103951 0.556056625 0.125770151 0.287315715 0.712649903
#> [61] 0.755516518 0.853557188 0.064330649 0.820695891 0.379224270 0.670170598
#> [67] 0.638946716 0.170540930 0.618103597 0.077436449 0.638946716 0.111507908
#> [73] 0.194335586 0.787874757 0.202542233 0.515829950 0.039883592 0.898106529
#> [79] 0.436395450 0.734063204 0.104200745 0.305210331 0.398200146 0.597312644
#> [85] 0.566326701 0.323382872 0.618103597 0.954419130 0.465814263 0.140631298
#> [91] 0.244140736 0.379224270 0.755516518 0.018133146 0.515829950 0.853557188
#> [97] 0.269817639 0.227149670 0.931778801 0.734063204 0.426639429 0.360355509
#> [103] 0.755516518 0.920488562 0.446211173 0.398200146 0.597312644 0.691373257
#> [109] 0.723342892 0.178461219 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 16 105 101 153 175 129 125 23 171 127 166 77 113
#> 8.71 19.75 9.97 21.33 21.91 23.41 15.65 16.92 16.57 3.53 19.98 7.27 22.86
#> 139 155 32 18 166.1 30 61 136 58 167 97 29 157
#> 21.49 13.08 20.90 15.21 19.98 17.43 10.12 21.83 19.34 15.55 19.14 15.45 15.10
#> 117 133 154 14 92 57 88 23.1 153.1 61.1 10 97.1 128
#> 17.46 14.65 12.63 12.89 22.92 14.46 18.37 16.92 21.33 10.12 10.53 19.14 20.35
#> 39 10.1 49 43 136.1 79 29.1 41 70 88.1 78 15 184
#> 15.59 10.53 12.19 12.10 21.83 16.23 15.45 18.02 7.38 18.37 23.88 22.68 17.77
#> 69 36 179 164 180 190 134 177 56 93 139.1 10.2 85
#> 23.23 21.19 18.63 23.60 14.82 20.81 17.81 12.53 12.21 10.33 21.49 10.53 16.44
#> 123 155.1 170 60 153.2 155.2 32.1 76 49.1 97.2 18.1 175.1 101.1
#> 13.00 13.08 19.54 13.15 21.33 13.08 20.90 19.22 12.19 19.14 15.21 21.91 9.97
#> 26 42 90 110 79.1 81 133.1 30.1 60.1 70.1 6 166.2 88.2
#> 15.77 12.43 20.94 17.56 16.23 14.06 14.65 17.43 13.15 7.38 15.64 19.98 18.37
#> 192 56.1 92.1 18.2 93.1 41.1 179.1 16.1 42.1 188 171.1 56.2 183
#> 16.44 12.21 22.92 15.21 10.33 18.02 18.63 8.71 12.43 16.16 16.57 12.21 9.24
#> 125.1 79.2 81.1 140 37 55 141 146 186 87 53 109 65
#> 15.65 16.23 14.06 12.68 12.52 19.34 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 161 143 165 120 44 7 33 200 34 120.1 116 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 174 64 1 33.1 137 28 126 182 126.1 163 119 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.1 132 83 116.1 112 83.1 33.2 72 120.2 200.1 185 131.1 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 138 173 200.2 156 74 54.1 64.1 33.3 33.4 104 12 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 119.1 48 35 20 141.2 74.1 54.2 198 44.1 131.2 186.1 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 21 135 143.1 182.1 11 186.2 147 27 112.1 198.1 80 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[57]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006310447 0.655363348 0.570432545
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.759112291 0.009413564 0.522585732
#> grade_iii, Cure model
#> 1.126499807
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 128 20.35 1 35 0 1
#> 13 14.34 1 54 0 1
#> 199 19.81 1 NA 0 1
#> 110 17.56 1 65 0 1
#> 89 11.44 1 NA 0 0
#> 81 14.06 1 34 0 0
#> 55 19.34 1 69 0 1
#> 125 15.65 1 67 1 0
#> 58 19.34 1 39 0 0
#> 49 12.19 1 48 1 0
#> 97 19.14 1 65 0 1
#> 106 16.67 1 49 1 0
#> 8 18.43 1 32 0 0
#> 171 16.57 1 41 0 1
#> 166 19.98 1 48 0 0
#> 51 18.23 1 83 0 1
#> 129 23.41 1 53 1 0
#> 136 21.83 1 43 0 1
#> 177 12.53 1 75 0 0
#> 39 15.59 1 37 0 1
#> 81.1 14.06 1 34 0 0
#> 153 21.33 1 55 1 0
#> 40 18.00 1 28 1 0
#> 158 20.14 1 74 1 0
#> 171.1 16.57 1 41 0 1
#> 124 9.73 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 59 10.16 1 NA 1 0
#> 124.1 9.73 1 NA 1 0
#> 128.1 20.35 1 35 0 1
#> 168 23.72 1 70 0 0
#> 18 15.21 1 49 1 0
#> 70 7.38 1 30 1 0
#> 114 13.68 1 NA 0 0
#> 43 12.10 1 61 0 1
#> 183 9.24 1 67 1 0
#> 189 10.51 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 129.1 23.41 1 53 1 0
#> 32.1 20.90 1 37 1 0
#> 69 23.23 1 25 0 1
#> 63 22.77 1 31 1 0
#> 70.1 7.38 1 30 1 0
#> 92 22.92 1 47 0 1
#> 110.1 17.56 1 65 0 1
#> 123 13.00 1 44 1 0
#> 36.1 21.19 1 48 0 1
#> 171.2 16.57 1 41 0 1
#> 79 16.23 1 54 1 0
#> 40.1 18.00 1 28 1 0
#> 90 20.94 1 50 0 1
#> 117 17.46 1 26 0 1
#> 90.1 20.94 1 50 0 1
#> 15 22.68 1 48 0 0
#> 177.1 12.53 1 75 0 0
#> 15.1 22.68 1 48 0 0
#> 169 22.41 1 46 0 0
#> 192 16.44 1 31 1 0
#> 39.1 15.59 1 37 0 1
#> 149 8.37 1 33 1 0
#> 106.1 16.67 1 49 1 0
#> 187 9.92 1 39 1 0
#> 41 18.02 1 40 1 0
#> 30 17.43 1 78 0 0
#> 40.2 18.00 1 28 1 0
#> 171.3 16.57 1 41 0 1
#> 117.1 17.46 1 26 0 1
#> 189.1 10.51 1 NA 1 0
#> 15.2 22.68 1 48 0 0
#> 25 6.32 1 34 1 0
#> 42 12.43 1 49 0 1
#> 169.1 22.41 1 46 0 0
#> 128.2 20.35 1 35 0 1
#> 10 10.53 1 34 0 0
#> 70.2 7.38 1 30 1 0
#> 24 23.89 1 38 0 0
#> 177.2 12.53 1 75 0 0
#> 18.1 15.21 1 49 1 0
#> 49.1 12.19 1 48 1 0
#> 59.1 10.16 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 194 22.40 1 38 0 1
#> 187.1 9.92 1 39 1 0
#> 123.1 13.00 1 44 1 0
#> 154 12.63 1 20 1 0
#> 41.1 18.02 1 40 1 0
#> 76 19.22 1 54 0 1
#> 51.1 18.23 1 83 0 1
#> 181 16.46 1 45 0 1
#> 128.3 20.35 1 35 0 1
#> 50 10.02 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 190 20.81 1 42 1 0
#> 100 16.07 1 60 0 0
#> 5 16.43 1 51 0 1
#> 129.2 23.41 1 53 1 0
#> 150 20.33 1 48 0 0
#> 26 15.77 1 49 0 1
#> 97.1 19.14 1 65 0 1
#> 30.1 17.43 1 78 0 0
#> 169.2 22.41 1 46 0 0
#> 93 10.33 1 52 0 1
#> 32.2 20.90 1 37 1 0
#> 66 22.13 1 53 0 0
#> 195 11.76 1 NA 1 0
#> 24.1 23.89 1 38 0 0
#> 110.2 17.56 1 65 0 1
#> 91 5.33 1 61 0 1
#> 184 17.77 1 38 0 0
#> 91.1 5.33 1 61 0 1
#> 66.1 22.13 1 53 0 0
#> 79.1 16.23 1 54 1 0
#> 48 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 193 24.00 0 45 0 1
#> 173 24.00 0 19 0 1
#> 121 24.00 0 57 1 0
#> 82 24.00 0 34 0 0
#> 102 24.00 0 49 0 0
#> 118 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 95 24.00 0 68 0 1
#> 122 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 178.1 24.00 0 52 1 0
#> 112 24.00 0 61 0 0
#> 54 24.00 0 53 1 0
#> 193.1 24.00 0 45 0 1
#> 62 24.00 0 71 0 0
#> 73 24.00 0 NA 0 1
#> 103 24.00 0 56 1 0
#> 17 24.00 0 38 0 1
#> 173.1 24.00 0 19 0 1
#> 146 24.00 0 63 1 0
#> 193.2 24.00 0 45 0 1
#> 35 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 48.1 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 176 24.00 0 43 0 1
#> 193.3 24.00 0 45 0 1
#> 109 24.00 0 48 0 0
#> 35.1 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 138 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 19.1 24.00 0 57 0 1
#> 73.1 24.00 0 NA 0 1
#> 71 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 53 24.00 0 32 0 1
#> 122.1 24.00 0 66 0 0
#> 126 24.00 0 48 0 0
#> 135 24.00 0 58 1 0
#> 82.1 24.00 0 34 0 0
#> 122.2 24.00 0 66 0 0
#> 109.1 24.00 0 48 0 0
#> 87 24.00 0 27 0 0
#> 53.1 24.00 0 32 0 1
#> 156 24.00 0 50 1 0
#> 102.1 24.00 0 49 0 0
#> 103.1 24.00 0 56 1 0
#> 20 24.00 0 46 1 0
#> 67 24.00 0 25 0 0
#> 121.1 24.00 0 57 1 0
#> 182 24.00 0 35 0 0
#> 132 24.00 0 55 0 0
#> 33 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 64 24.00 0 43 0 0
#> 38 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 28.1 24.00 0 67 1 0
#> 73.2 24.00 0 NA 0 1
#> 115 24.00 0 NA 1 0
#> 163.1 24.00 0 66 0 0
#> 112.1 24.00 0 61 0 0
#> 2 24.00 0 9 0 0
#> 21 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 102.2 24.00 0 49 0 0
#> 20.1 24.00 0 46 1 0
#> 112.2 24.00 0 61 0 0
#> 47 24.00 0 38 0 1
#> 143.1 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 84.1 24.00 0 39 0 1
#> 137.1 24.00 0 45 1 0
#> 3.1 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 34 24.00 0 36 0 0
#> 3.2 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 64.1 24.00 0 43 0 0
#> 22 24.00 0 52 1 0
#> 98.1 24.00 0 34 1 0
#> 73.3 24.00 0 NA 0 1
#> 152 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.759 NA NA NA
#> 2 age, Cure model 0.00941 NA NA NA
#> 3 grade_ii, Cure model 0.523 NA NA NA
#> 4 grade_iii, Cure model 1.13 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00631 NA NA NA
#> 2 grade_ii, Survival model 0.655 NA NA NA
#> 3 grade_iii, Survival model 0.570 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.759112 0.009414 0.522586 1.126500
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 253.3
#> Residual Deviance: 244.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.759112291 0.009413564 0.522585732 1.126499807
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006310447 0.655363348 0.570432545
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.55992420 0.87277430 0.72465005 0.87804617 0.62036724 0.84582860
#> [7] 0.62036724 0.92914833 0.64491318 0.76977709 0.66039295 0.78216004
#> [13] 0.61186764 0.66815825 0.20379152 0.45234774 0.90395034 0.85134429
#> [19] 0.87804617 0.46519422 0.69722617 0.60332607 0.78216004 0.52131040
#> [25] 0.55992420 0.15965881 0.86216739 0.97261551 0.93899609 0.96317457
#> [31] 0.47745664 0.20379152 0.52131040 0.26076335 0.29707930 0.97261551
#> [37] 0.27973238 0.72465005 0.88852824 0.47745664 0.78216004 0.82332785
#> [43] 0.69722617 0.50006784 0.74420974 0.50006784 0.31316624 0.90395034
#> [49] 0.31316624 0.35674907 0.81168210 0.85134429 0.96791083 0.76977709
#> [55] 0.95363459 0.68292085 0.75706204 0.69722617 0.78216004 0.74420974
#> [61] 0.31316624 0.98639724 0.91909017 0.35674907 0.55992420 0.94389178
#> [67] 0.97261551 0.07269347 0.90395034 0.86216739 0.92914833 0.92412555
#> [73] 0.39861741 0.95363459 0.88852824 0.89882302 0.68292085 0.63679987
#> [79] 0.66815825 0.80577217 0.55992420 0.43900079 0.55033374 0.83460308
#> [85] 0.81753485 0.20379152 0.59452636 0.84024227 0.64491318 0.75706204
#> [91] 0.35674907 0.94878139 0.52131040 0.41246515 0.07269347 0.72465005
#> [97] 0.99098296 0.71775783 0.99098296 0.41246515 0.82332785 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 128 13 110 81 55 125 58 49 97 106 8 171 166
#> 20.35 14.34 17.56 14.06 19.34 15.65 19.34 12.19 19.14 16.67 18.43 16.57 19.98
#> 51 129 136 177 39 81.1 153 40 158 171.1 32 128.1 168
#> 18.23 23.41 21.83 12.53 15.59 14.06 21.33 18.00 20.14 16.57 20.90 20.35 23.72
#> 18 70 43 183 36 129.1 32.1 69 63 70.1 92 110.1 123
#> 15.21 7.38 12.10 9.24 21.19 23.41 20.90 23.23 22.77 7.38 22.92 17.56 13.00
#> 36.1 171.2 79 40.1 90 117 90.1 15 177.1 15.1 169 192 39.1
#> 21.19 16.57 16.23 18.00 20.94 17.46 20.94 22.68 12.53 22.68 22.41 16.44 15.59
#> 149 106.1 187 41 30 40.2 171.3 117.1 15.2 25 42 169.1 128.2
#> 8.37 16.67 9.92 18.02 17.43 18.00 16.57 17.46 22.68 6.32 12.43 22.41 20.35
#> 10 70.2 24 177.2 18.1 49.1 56 194 187.1 123.1 154 41.1 76
#> 10.53 7.38 23.89 12.53 15.21 12.19 12.21 22.40 9.92 13.00 12.63 18.02 19.22
#> 51.1 181 128.3 175 190 100 5 129.2 150 26 97.1 30.1 169.2
#> 18.23 16.46 20.35 21.91 20.81 16.07 16.43 23.41 20.33 15.77 19.14 17.43 22.41
#> 93 32.2 66 24.1 110.2 91 184 91.1 66.1 79.1 48 3 163
#> 10.33 20.90 22.13 23.89 17.56 5.33 17.77 5.33 22.13 16.23 24.00 24.00 24.00
#> 178 193 173 121 82 102 118 174 95 122 143 178.1 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 193.1 62 103 17 173.1 146 193.2 35 200 48.1 19 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.3 109 35.1 119 138 98 19.1 71 137 53 122.1 126 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 122.2 109.1 87 53.1 156 102.1 103.1 20 67 121.1 182 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 28 64 38 44 28.1 163.1 112.1 2 21 84 102.2 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.2 47 143.1 142 84.1 137.1 3.1 148 34 3.2 1 64.1 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 152
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[58]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003874011 0.704914867 0.416050376
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.00246355 0.01640588 0.44914986
#> grade_iii, Cure model
#> 0.68807214
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 167 15.55 1 56 1 0
#> 168 23.72 1 70 0 0
#> 29 15.45 1 68 1 0
#> 42 12.43 1 49 0 1
#> 179 18.63 1 42 0 0
#> 85 16.44 1 36 0 0
#> 51 18.23 1 83 0 1
#> 108 18.29 1 39 0 1
#> 190 20.81 1 42 1 0
#> 56 12.21 1 60 0 0
#> 60 13.15 1 38 1 0
#> 60.1 13.15 1 38 1 0
#> 181 16.46 1 45 0 1
#> 166 19.98 1 48 0 0
#> 43 12.10 1 61 0 1
#> 107 11.18 1 54 1 0
#> 8 18.43 1 32 0 0
#> 30 17.43 1 78 0 0
#> 194 22.40 1 38 0 1
#> 167.1 15.55 1 56 1 0
#> 139 21.49 1 63 1 0
#> 150 20.33 1 48 0 0
#> 26 15.77 1 49 0 1
#> 171 16.57 1 41 0 1
#> 96 14.54 1 33 0 1
#> 70 7.38 1 30 1 0
#> 170 19.54 1 43 0 1
#> 58 19.34 1 39 0 0
#> 76 19.22 1 54 0 1
#> 51.1 18.23 1 83 0 1
#> 97 19.14 1 65 0 1
#> 145 10.07 1 65 1 0
#> 171.1 16.57 1 41 0 1
#> 57 14.46 1 45 0 1
#> 179.1 18.63 1 42 0 0
#> 114 13.68 1 NA 0 0
#> 91 5.33 1 61 0 1
#> 93 10.33 1 52 0 1
#> 145.1 10.07 1 65 1 0
#> 114.1 13.68 1 NA 0 0
#> 25 6.32 1 34 1 0
#> 189 10.51 1 NA 1 0
#> 145.2 10.07 1 65 1 0
#> 134 17.81 1 47 1 0
#> 124 9.73 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 93.1 10.33 1 52 0 1
#> 139.1 21.49 1 63 1 0
#> 187 9.92 1 39 1 0
#> 93.2 10.33 1 52 0 1
#> 140 12.68 1 59 1 0
#> 128 20.35 1 35 0 1
#> 123 13.00 1 44 1 0
#> 136 21.83 1 43 0 1
#> 129 23.41 1 53 1 0
#> 24 23.89 1 38 0 0
#> 99 21.19 1 38 0 1
#> 175 21.91 1 43 0 0
#> 106 16.67 1 49 1 0
#> 81 14.06 1 34 0 0
#> 66 22.13 1 53 0 0
#> 76.1 19.22 1 54 0 1
#> 108.1 18.29 1 39 0 1
#> 43.1 12.10 1 61 0 1
#> 195 11.76 1 NA 1 0
#> 29.1 15.45 1 68 1 0
#> 42.1 12.43 1 49 0 1
#> 139.2 21.49 1 63 1 0
#> 59 10.16 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 6 15.64 1 39 0 0
#> 55 19.34 1 69 0 1
#> 123.1 13.00 1 44 1 0
#> 32 20.90 1 37 1 0
#> 140.1 12.68 1 59 1 0
#> 57.1 14.46 1 45 0 1
#> 133 14.65 1 57 0 0
#> 10 10.53 1 34 0 0
#> 124.1 9.73 1 NA 1 0
#> 106.1 16.67 1 49 1 0
#> 90 20.94 1 50 0 1
#> 55.1 19.34 1 69 0 1
#> 90.1 20.94 1 50 0 1
#> 133.1 14.65 1 57 0 0
#> 154 12.63 1 20 1 0
#> 164 23.60 1 76 0 1
#> 8.1 18.43 1 32 0 0
#> 139.3 21.49 1 63 1 0
#> 175.1 21.91 1 43 0 0
#> 69.1 23.23 1 25 0 1
#> 190.1 20.81 1 42 1 0
#> 181.1 16.46 1 45 0 1
#> 125 15.65 1 67 1 0
#> 89 11.44 1 NA 0 0
#> 170.1 19.54 1 43 0 1
#> 105 19.75 1 60 0 0
#> 40 18.00 1 28 1 0
#> 88 18.37 1 47 0 0
#> 166.1 19.98 1 48 0 0
#> 68 20.62 1 44 0 0
#> 78 23.88 1 43 0 0
#> 140.2 12.68 1 59 1 0
#> 50 10.02 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 175.2 21.91 1 43 0 0
#> 29.2 15.45 1 68 1 0
#> 55.2 19.34 1 69 0 1
#> 125.1 15.65 1 67 1 0
#> 96.1 14.54 1 33 0 1
#> 134.1 17.81 1 47 1 0
#> 136.1 21.83 1 43 0 1
#> 63 22.77 1 31 1 0
#> 22 24.00 0 52 1 0
#> 132 24.00 0 55 0 0
#> 162 24.00 0 51 0 0
#> 46 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 27 24.00 0 63 1 0
#> 102 24.00 0 49 0 0
#> 120 24.00 0 68 0 1
#> 104 24.00 0 50 1 0
#> 137 24.00 0 45 1 0
#> 152 24.00 0 36 0 1
#> 74 24.00 0 43 0 1
#> 38 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 80 24.00 0 41 0 0
#> 46.1 24.00 0 71 0 0
#> 1 24.00 0 23 1 0
#> 9 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 7 24.00 0 37 1 0
#> 53 24.00 0 32 0 1
#> 196 24.00 0 19 0 0
#> 146 24.00 0 63 1 0
#> 152.1 24.00 0 36 0 1
#> 112.1 24.00 0 61 0 0
#> 109 24.00 0 48 0 0
#> 53.1 24.00 0 32 0 1
#> 53.2 24.00 0 32 0 1
#> 21 24.00 0 47 0 0
#> 151 24.00 0 42 0 0
#> 65.1 24.00 0 57 1 0
#> 119 24.00 0 17 0 0
#> 7.1 24.00 0 37 1 0
#> 12 24.00 0 63 0 0
#> 47 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 80.1 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 109.1 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 35 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 198 24.00 0 66 0 1
#> 53.3 24.00 0 32 0 1
#> 120.1 24.00 0 68 0 1
#> 95 24.00 0 68 0 1
#> 116 24.00 0 58 0 1
#> 73 24.00 0 NA 0 1
#> 141 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 162.1 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 22.1 24.00 0 52 1 0
#> 141.1 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 1.1 24.00 0 23 1 0
#> 142 24.00 0 53 0 0
#> 193.1 24.00 0 45 0 1
#> 120.2 24.00 0 68 0 1
#> 116.1 24.00 0 58 0 1
#> 152.2 24.00 0 36 0 1
#> 174.1 24.00 0 49 1 0
#> 118 24.00 0 44 1 0
#> 174.2 24.00 0 49 1 0
#> 144 24.00 0 28 0 1
#> 72.1 24.00 0 40 0 1
#> 48 24.00 0 31 1 0
#> 112.2 24.00 0 61 0 0
#> 67.1 24.00 0 25 0 0
#> 33 24.00 0 53 0 0
#> 12.1 24.00 0 63 0 0
#> 72.2 24.00 0 40 0 1
#> 64 24.00 0 43 0 0
#> 132.1 24.00 0 55 0 0
#> 65.2 24.00 0 57 1 0
#> 31.1 24.00 0 36 0 1
#> 62 24.00 0 71 0 0
#> 151.1 24.00 0 42 0 0
#> 87 24.00 0 27 0 0
#> 67.2 24.00 0 25 0 0
#> 48.1 24.00 0 31 1 0
#> 146.1 24.00 0 63 1 0
#> 27.1 24.00 0 63 1 0
#> 119.1 24.00 0 17 0 0
#> 94 24.00 0 51 0 1
#> 135 24.00 0 58 1 0
#> 62.1 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.00 NA NA NA
#> 2 age, Cure model 0.0164 NA NA NA
#> 3 grade_ii, Cure model 0.449 NA NA NA
#> 4 grade_iii, Cure model 0.688 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00387 NA NA NA
#> 2 grade_ii, Survival model 0.705 NA NA NA
#> 3 grade_iii, Survival model 0.416 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00246 0.01641 0.44915 0.68807
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 252.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00246355 0.01640588 0.44914986 0.68807214
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003874011 0.704914867 0.416050376
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.78661444 0.11047296 0.79969442 0.90835173 0.59895547 0.75249468
#> [7] 0.65647503 0.64032313 0.44459856 0.91957713 0.86179062 0.86179062
#> [13] 0.73854120 0.49302469 0.92519806 0.93628223 0.61552456 0.69501538
#> [19] 0.25041482 0.78661444 0.35721206 0.48343232 0.75949430 0.72437233
#> [25] 0.83101129 0.98447529 0.52134171 0.53958524 0.57369683 0.65647503
#> [31] 0.59057157 0.96347721 0.72437233 0.84340355 0.59895547 0.99485337
#> [37] 0.94729709 0.96347721 0.98968213 0.96347721 0.68000102 0.70253474
#> [43] 0.94729709 0.35721206 0.97923315 0.94729709 0.88557657 0.47380091
#> [49] 0.87379687 0.32853983 0.17320930 0.03039519 0.40148421 0.28344871
#> [55] 0.70998483 0.85565102 0.26704798 0.57369683 0.64032313 0.92519806
#> [61] 0.79969442 0.90835173 0.35721206 0.19575837 0.77987671 0.53958524
#> [67] 0.87379687 0.43413967 0.88557657 0.84340355 0.81848402 0.94179192
#> [73] 0.70998483 0.41279554 0.53958524 0.41279554 0.81848402 0.90266285
#> [79] 0.14527673 0.61552456 0.35721206 0.28344871 0.19575837 0.44459856
#> [85] 0.73854120 0.76644061 0.52134171 0.51187446 0.67220479 0.63203503
#> [91] 0.49302469 0.46402319 0.07205250 0.88557657 0.28344871 0.79969442
#> [97] 0.53958524 0.76644061 0.83101129 0.68000102 0.32853983 0.23290261
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 167 168 29 42 179 85 51 108 190 56 60 60.1 181
#> 15.55 23.72 15.45 12.43 18.63 16.44 18.23 18.29 20.81 12.21 13.15 13.15 16.46
#> 166 43 107 8 30 194 167.1 139 150 26 171 96 70
#> 19.98 12.10 11.18 18.43 17.43 22.40 15.55 21.49 20.33 15.77 16.57 14.54 7.38
#> 170 58 76 51.1 97 145 171.1 57 179.1 91 93 145.1 25
#> 19.54 19.34 19.22 18.23 19.14 10.07 16.57 14.46 18.63 5.33 10.33 10.07 6.32
#> 145.2 134 45 93.1 139.1 187 93.2 140 128 123 136 129 24
#> 10.07 17.81 17.42 10.33 21.49 9.92 10.33 12.68 20.35 13.00 21.83 23.41 23.89
#> 99 175 106 81 66 76.1 108.1 43.1 29.1 42.1 139.2 69 6
#> 21.19 21.91 16.67 14.06 22.13 19.22 18.29 12.10 15.45 12.43 21.49 23.23 15.64
#> 55 123.1 32 140.1 57.1 133 10 106.1 90 55.1 90.1 133.1 154
#> 19.34 13.00 20.90 12.68 14.46 14.65 10.53 16.67 20.94 19.34 20.94 14.65 12.63
#> 164 8.1 139.3 175.1 69.1 190.1 181.1 125 170.1 105 40 88 166.1
#> 23.60 18.43 21.49 21.91 23.23 20.81 16.46 15.65 19.54 19.75 18.00 18.37 19.98
#> 68 78 140.2 175.2 29.2 55.2 125.1 96.1 134.1 136.1 63 22 132
#> 20.62 23.88 12.68 21.91 15.45 19.34 15.65 14.54 17.81 21.83 22.77 24.00 24.00
#> 162 46 31 27 102 120 104 137 152 74 38 112 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1 1 9 65 7 53 196 146 152.1 112.1 109 53.1 53.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 151 65.1 119 7.1 12 47 147 80.1 72 109.1 83 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 198 53.3 120.1 95 116 141 67 162.1 3 22.1 141.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 142 193.1 120.2 116.1 152.2 174.1 118 174.2 144 72.1 48 112.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 33 12.1 72.2 64 132.1 65.2 31.1 62 151.1 87 67.2 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146.1 27.1 119.1 94 135 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[59]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003502825 0.548328709 0.242910381
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.25888644 0.02188973 -0.01784941
#> grade_iii, Cure model
#> 1.41301154
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 134 17.81 1 47 1 0
#> 158 20.14 1 74 1 0
#> 26 15.77 1 49 0 1
#> 52 10.42 1 52 0 1
#> 43 12.10 1 61 0 1
#> 159 10.55 1 50 0 1
#> 49 12.19 1 48 1 0
#> 195 11.76 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 194 22.40 1 38 0 1
#> 125 15.65 1 67 1 0
#> 91 5.33 1 61 0 1
#> 85 16.44 1 36 0 0
#> 58 19.34 1 39 0 0
#> 125.1 15.65 1 67 1 0
#> 125.2 15.65 1 67 1 0
#> 5 16.43 1 51 0 1
#> 50 10.02 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 78 23.88 1 43 0 0
#> 6 15.64 1 39 0 0
#> 128 20.35 1 35 0 1
#> 145 10.07 1 65 1 0
#> 42 12.43 1 49 0 1
#> 86 23.81 1 58 0 1
#> 133 14.65 1 57 0 0
#> 171 16.57 1 41 0 1
#> 79 16.23 1 54 1 0
#> 88 18.37 1 47 0 0
#> 150 20.33 1 48 0 0
#> 36 21.19 1 48 0 1
#> 128.1 20.35 1 35 0 1
#> 194.1 22.40 1 38 0 1
#> 63 22.77 1 31 1 0
#> 61 10.12 1 36 0 1
#> 89 11.44 1 NA 0 0
#> 76 19.22 1 54 0 1
#> 154 12.63 1 20 1 0
#> 128.2 20.35 1 35 0 1
#> 96 14.54 1 33 0 1
#> 188 16.16 1 46 0 1
#> 97 19.14 1 65 0 1
#> 92 22.92 1 47 0 1
#> 4.1 17.64 1 NA 0 1
#> 99 21.19 1 38 0 1
#> 177 12.53 1 75 0 0
#> 155 13.08 1 26 0 0
#> 36.1 21.19 1 48 0 1
#> 150.1 20.33 1 48 0 0
#> 136 21.83 1 43 0 1
#> 77 7.27 1 67 0 1
#> 177.1 12.53 1 75 0 0
#> 90 20.94 1 50 0 1
#> 155.1 13.08 1 26 0 0
#> 179 18.63 1 42 0 0
#> 187 9.92 1 39 1 0
#> 113 22.86 1 34 0 0
#> 79.1 16.23 1 54 1 0
#> 42.1 12.43 1 49 0 1
#> 170 19.54 1 43 0 1
#> 158.1 20.14 1 74 1 0
#> 113.1 22.86 1 34 0 0
#> 197 21.60 1 69 1 0
#> 56 12.21 1 60 0 0
#> 140 12.68 1 59 1 0
#> 41 18.02 1 40 1 0
#> 164 23.60 1 76 0 1
#> 101 9.97 1 10 0 1
#> 89.1 11.44 1 NA 0 0
#> 15 22.68 1 48 0 0
#> 13 14.34 1 54 0 1
#> 29 15.45 1 68 1 0
#> 40 18.00 1 28 1 0
#> 192.1 16.44 1 31 1 0
#> 66 22.13 1 53 0 0
#> 140.1 12.68 1 59 1 0
#> 183 9.24 1 67 1 0
#> 51 18.23 1 83 0 1
#> 175 21.91 1 43 0 0
#> 134.1 17.81 1 47 1 0
#> 117 17.46 1 26 0 1
#> 154.1 12.63 1 20 1 0
#> 130 16.47 1 53 0 1
#> 114 13.68 1 NA 0 0
#> 4.2 17.64 1 NA 0 1
#> 154.2 12.63 1 20 1 0
#> 107 11.18 1 54 1 0
#> 187.1 9.92 1 39 1 0
#> 169 22.41 1 46 0 0
#> 157 15.10 1 47 0 0
#> 157.1 15.10 1 47 0 0
#> 177.2 12.53 1 75 0 0
#> 199 19.81 1 NA 0 1
#> 145.1 10.07 1 65 1 0
#> 101.1 9.97 1 10 0 1
#> 63.1 22.77 1 31 1 0
#> 188.1 16.16 1 46 0 1
#> 61.1 10.12 1 36 0 1
#> 4.3 17.64 1 NA 0 1
#> 36.2 21.19 1 48 0 1
#> 13.1 14.34 1 54 0 1
#> 127 3.53 1 62 0 1
#> 77.1 7.27 1 67 0 1
#> 30 17.43 1 78 0 0
#> 4.4 17.64 1 NA 0 1
#> 58.1 19.34 1 39 0 0
#> 105 19.75 1 60 0 0
#> 45 17.42 1 54 0 1
#> 127.1 3.53 1 62 0 1
#> 101.2 9.97 1 10 0 1
#> 39 15.59 1 37 0 1
#> 56.1 12.21 1 60 0 0
#> 103 24.00 0 56 1 0
#> 137 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#> 160 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 35 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 17 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 7 24.00 0 37 1 0
#> 193 24.00 0 45 0 1
#> 143.1 24.00 0 51 0 0
#> 143.2 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 138.1 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 148 24.00 0 61 1 0
#> 141 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 27 24.00 0 63 1 0
#> 82 24.00 0 34 0 0
#> 135 24.00 0 58 1 0
#> 22 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 191.1 24.00 0 60 0 1
#> 83 24.00 0 6 0 0
#> 120 24.00 0 68 0 1
#> 120.1 24.00 0 68 0 1
#> 94 24.00 0 51 0 1
#> 47 24.00 0 38 0 1
#> 83.1 24.00 0 6 0 0
#> 20.1 24.00 0 46 1 0
#> 112 24.00 0 61 0 0
#> 103.1 24.00 0 56 1 0
#> 1 24.00 0 23 1 0
#> 131 24.00 0 66 0 0
#> 7.1 24.00 0 37 1 0
#> 98 24.00 0 34 1 0
#> 156 24.00 0 50 1 0
#> 178.1 24.00 0 52 1 0
#> 151 24.00 0 42 0 0
#> 112.1 24.00 0 61 0 0
#> 118 24.00 0 44 1 0
#> 83.2 24.00 0 6 0 0
#> 34 24.00 0 36 0 0
#> 193.1 24.00 0 45 0 1
#> 137.1 24.00 0 45 1 0
#> 161 24.00 0 45 0 0
#> 44 24.00 0 56 0 0
#> 102 24.00 0 49 0 0
#> 165 24.00 0 47 0 0
#> 138.2 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 143.3 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 21.1 24.00 0 47 0 0
#> 185 24.00 0 44 1 0
#> 161.1 24.00 0 45 0 0
#> 35.1 24.00 0 51 0 0
#> 34.1 24.00 0 36 0 0
#> 71 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 83.3 24.00 0 6 0 0
#> 2.1 24.00 0 9 0 0
#> 67.1 24.00 0 25 0 0
#> 34.2 24.00 0 36 0 0
#> 119 24.00 0 17 0 0
#> 82.1 24.00 0 34 0 0
#> 35.2 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 103.2 24.00 0 56 1 0
#> 196 24.00 0 19 0 0
#> 172 24.00 0 41 0 0
#> 103.3 24.00 0 56 1 0
#> 38 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 1.1 24.00 0 23 1 0
#> 48.1 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 38.1 24.00 0 31 1 0
#> 22.1 24.00 0 52 1 0
#> 72.1 24.00 0 40 0 1
#> 121 24.00 0 57 1 0
#> 148.1 24.00 0 61 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.26 NA NA NA
#> 2 age, Cure model 0.0219 NA NA NA
#> 3 grade_ii, Cure model -0.0178 NA NA NA
#> 4 grade_iii, Cure model 1.41 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00350 NA NA NA
#> 2 grade_ii, Survival model 0.548 NA NA NA
#> 3 grade_iii, Survival model 0.243 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.25889 0.02189 -0.01785 1.41301
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 261.1
#> Residual Deviance: 237.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.25888644 0.02188973 -0.01784941 1.41301154
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003502825 0.548328709 0.242910381
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.54585702 0.41744740 0.67340828 0.89708018 0.87677075 0.89034701
#> [7] 0.86992337 0.60780524 0.22487232 0.68141179 0.98125267 0.60780524
#> [13] 0.45818329 0.68141179 0.68141179 0.63280645 0.02535765 0.70419882
#> [19] 0.36339811 0.91706232 0.84236396 0.05993458 0.74196504 0.59035454
#> [25] 0.64119372 0.50767448 0.39577583 0.30691565 0.36339811 0.22487232
#> [31] 0.16458381 0.90378668 0.47809707 0.80060913 0.36339811 0.74945392
#> [37] 0.65739922 0.48804670 0.10864967 0.30691565 0.82156623 0.77159514
#> [43] 0.30691565 0.39577583 0.28043925 0.96865988 0.82156623 0.35179861
#> [49] 0.77159514 0.49787592 0.94949824 0.12874832 0.64119372 0.84236396
#> [55] 0.44805068 0.41744740 0.12874832 0.29403571 0.85616960 0.78625302
#> [61] 0.52707595 0.08651029 0.93011633 0.19442658 0.75691067 0.71949547
#> [67] 0.53654115 0.60780524 0.25247675 0.78625302 0.96229203 0.51743933
#> [73] 0.26651751 0.54585702 0.56370182 0.80060913 0.59911388 0.80060913
#> [79] 0.88358732 0.94949824 0.20974574 0.72702972 0.72702972 0.82156623
#> [85] 0.91706232 0.93011633 0.16458381 0.65739922 0.90378668 0.30691565
#> [91] 0.75691067 0.98754596 0.96865988 0.57263944 0.45818329 0.43780638
#> [97] 0.58153344 0.98754596 0.93011633 0.71186569 0.85616960 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 134 158 26 52 43 159 49 192 194 125 91 85 58
#> 17.81 20.14 15.77 10.42 12.10 10.55 12.19 16.44 22.40 15.65 5.33 16.44 19.34
#> 125.1 125.2 5 78 6 128 145 42 86 133 171 79 88
#> 15.65 15.65 16.43 23.88 15.64 20.35 10.07 12.43 23.81 14.65 16.57 16.23 18.37
#> 150 36 128.1 194.1 63 61 76 154 128.2 96 188 97 92
#> 20.33 21.19 20.35 22.40 22.77 10.12 19.22 12.63 20.35 14.54 16.16 19.14 22.92
#> 99 177 155 36.1 150.1 136 77 177.1 90 155.1 179 187 113
#> 21.19 12.53 13.08 21.19 20.33 21.83 7.27 12.53 20.94 13.08 18.63 9.92 22.86
#> 79.1 42.1 170 158.1 113.1 197 56 140 41 164 101 15 13
#> 16.23 12.43 19.54 20.14 22.86 21.60 12.21 12.68 18.02 23.60 9.97 22.68 14.34
#> 29 40 192.1 66 140.1 183 51 175 134.1 117 154.1 130 154.2
#> 15.45 18.00 16.44 22.13 12.68 9.24 18.23 21.91 17.81 17.46 12.63 16.47 12.63
#> 107 187.1 169 157 157.1 177.2 145.1 101.1 63.1 188.1 61.1 36.2 13.1
#> 11.18 9.92 22.41 15.10 15.10 12.53 10.07 9.97 22.77 16.16 10.12 21.19 14.34
#> 127 77.1 30 58.1 105 45 127.1 101.2 39 56.1 103 137 95
#> 3.53 7.27 17.43 19.34 19.75 17.42 3.53 9.97 15.59 12.21 24.00 24.00 24.00
#> 160 143 178 20 35 138 48 191 17 2 7 193 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.2 21 138.1 67 148 141 33 27 82 135 22 87 191.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 120 120.1 94 47 83.1 20.1 112 103.1 1 131 7.1 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 178.1 151 112.1 118 83.2 34 193.1 137.1 161 44 102 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.2 173 143.3 9 21.1 185 161.1 35.1 34.1 71 104 83.3 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 34.2 119 82.1 35.2 19 103.2 196 172 103.3 38 141.1 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 72 38.1 22.1 72.1 121 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[60]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004906045 0.489303145 0.230328716
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.551196215 0.009279751 -0.150786725
#> grade_iii, Cure model
#> 0.870364664
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 169 22.41 1 46 0 0
#> 86 23.81 1 58 0 1
#> 76 19.22 1 54 0 1
#> 199 19.81 1 NA 0 1
#> 100 16.07 1 60 0 0
#> 90 20.94 1 50 0 1
#> 145 10.07 1 65 1 0
#> 39 15.59 1 37 0 1
#> 43 12.10 1 61 0 1
#> 16 8.71 1 71 0 1
#> 194 22.40 1 38 0 1
#> 199.1 19.81 1 NA 0 1
#> 113 22.86 1 34 0 0
#> 181 16.46 1 45 0 1
#> 23 16.92 1 61 0 0
#> 166 19.98 1 48 0 0
#> 134 17.81 1 47 1 0
#> 88 18.37 1 47 0 0
#> 10 10.53 1 34 0 0
#> 52 10.42 1 52 0 1
#> 91 5.33 1 61 0 1
#> 145.1 10.07 1 65 1 0
#> 97 19.14 1 65 0 1
#> 8 18.43 1 32 0 0
#> 183 9.24 1 67 1 0
#> 154 12.63 1 20 1 0
#> 179 18.63 1 42 0 0
#> 100.1 16.07 1 60 0 0
#> 69 23.23 1 25 0 1
#> 45 17.42 1 54 0 1
#> 13 14.34 1 54 0 1
#> 150 20.33 1 48 0 0
#> 113.1 22.86 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 76.1 19.22 1 54 0 1
#> 154.1 12.63 1 20 1 0
#> 101 9.97 1 10 0 1
#> 89 11.44 1 NA 0 0
#> 99 21.19 1 38 0 1
#> 101.1 9.97 1 10 0 1
#> 189 10.51 1 NA 1 0
#> 16.1 8.71 1 71 0 1
#> 16.2 8.71 1 71 0 1
#> 10.1 10.53 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 97.1 19.14 1 65 0 1
#> 92 22.92 1 47 0 1
#> 26 15.77 1 49 0 1
#> 190 20.81 1 42 1 0
#> 4.1 17.64 1 NA 0 1
#> 57 14.46 1 45 0 1
#> 24 23.89 1 38 0 0
#> 52.1 10.42 1 52 0 1
#> 36 21.19 1 48 0 1
#> 166.1 19.98 1 48 0 0
#> 167 15.55 1 56 1 0
#> 88.1 18.37 1 47 0 0
#> 199.2 19.81 1 NA 0 1
#> 149 8.37 1 33 1 0
#> 68 20.62 1 44 0 0
#> 55 19.34 1 69 0 1
#> 188 16.16 1 46 0 1
#> 153 21.33 1 55 1 0
#> 197 21.60 1 69 1 0
#> 111 17.45 1 47 0 1
#> 55.1 19.34 1 69 0 1
#> 195.1 11.76 1 NA 1 0
#> 181.1 16.46 1 45 0 1
#> 50 10.02 1 NA 1 0
#> 45.1 17.42 1 54 0 1
#> 139 21.49 1 63 1 0
#> 88.2 18.37 1 47 0 0
#> 166.2 19.98 1 48 0 0
#> 32 20.90 1 37 1 0
#> 90.1 20.94 1 50 0 1
#> 24.1 23.89 1 38 0 0
#> 92.1 22.92 1 47 0 1
#> 177 12.53 1 75 0 0
#> 66 22.13 1 53 0 0
#> 15 22.68 1 48 0 0
#> 188.1 16.16 1 46 0 1
#> 100.2 16.07 1 60 0 0
#> 30 17.43 1 78 0 0
#> 68.1 20.62 1 44 0 0
#> 18 15.21 1 49 1 0
#> 149.1 8.37 1 33 1 0
#> 60 13.15 1 38 1 0
#> 50.1 10.02 1 NA 1 0
#> 10.2 10.53 1 34 0 0
#> 89.1 11.44 1 NA 0 0
#> 171 16.57 1 41 0 1
#> 167.1 15.55 1 56 1 0
#> 188.2 16.16 1 46 0 1
#> 114 13.68 1 NA 0 0
#> 68.2 20.62 1 44 0 0
#> 139.1 21.49 1 63 1 0
#> 86.1 23.81 1 58 0 1
#> 8.1 18.43 1 32 0 0
#> 52.2 10.42 1 52 0 1
#> 194.1 22.40 1 38 0 1
#> 100.3 16.07 1 60 0 0
#> 179.1 18.63 1 42 0 0
#> 18.1 15.21 1 49 1 0
#> 136 21.83 1 43 0 1
#> 170 19.54 1 43 0 1
#> 139.2 21.49 1 63 1 0
#> 42 12.43 1 49 0 1
#> 40 18.00 1 28 1 0
#> 57.1 14.46 1 45 0 1
#> 199.3 19.81 1 NA 0 1
#> 56 12.21 1 60 0 0
#> 21 24.00 0 47 0 0
#> 165 24.00 0 47 0 0
#> 198 24.00 0 66 0 1
#> 109 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 31 24.00 0 36 0 1
#> 186 24.00 0 45 1 0
#> 44 24.00 0 56 0 0
#> 19 24.00 0 57 0 1
#> 121 24.00 0 57 1 0
#> 17 24.00 0 38 0 1
#> 38 24.00 0 31 1 0
#> 186.1 24.00 0 45 1 0
#> 137 24.00 0 45 1 0
#> 144 24.00 0 28 0 1
#> 44.1 24.00 0 56 0 0
#> 17.1 24.00 0 38 0 1
#> 47 24.00 0 38 0 1
#> 131 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 80 24.00 0 41 0 0
#> 87 24.00 0 27 0 0
#> 72.1 24.00 0 40 0 1
#> 141 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 102 24.00 0 49 0 0
#> 191 24.00 0 60 0 1
#> 198.1 24.00 0 66 0 1
#> 9 24.00 0 31 1 0
#> 44.2 24.00 0 56 0 0
#> 22.1 24.00 0 52 1 0
#> 132 24.00 0 55 0 0
#> 2 24.00 0 9 0 0
#> 148 24.00 0 61 1 0
#> 176 24.00 0 43 0 1
#> 173 24.00 0 19 0 1
#> 21.1 24.00 0 47 0 0
#> 73 24.00 0 NA 0 1
#> 7 24.00 0 37 1 0
#> 34 24.00 0 36 0 0
#> 132.1 24.00 0 55 0 0
#> 33 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 54 24.00 0 53 1 0
#> 142 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 67 24.00 0 25 0 0
#> 94 24.00 0 51 0 1
#> 73.1 24.00 0 NA 0 1
#> 119 24.00 0 17 0 0
#> 12 24.00 0 63 0 0
#> 44.3 24.00 0 56 0 0
#> 44.4 24.00 0 56 0 0
#> 35 24.00 0 51 0 0
#> 21.2 24.00 0 47 0 0
#> 34.1 24.00 0 36 0 0
#> 53 24.00 0 32 0 1
#> 38.1 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 138 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 3 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 44.5 24.00 0 56 0 0
#> 185.1 24.00 0 44 1 0
#> 67.1 24.00 0 25 0 0
#> 121.1 24.00 0 57 1 0
#> 17.2 24.00 0 38 0 1
#> 176.1 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 115 24.00 0 NA 1 0
#> 103 24.00 0 56 1 0
#> 185.2 24.00 0 44 1 0
#> 115.1 24.00 0 NA 1 0
#> 2.1 24.00 0 9 0 0
#> 116 24.00 0 58 0 1
#> 160 24.00 0 31 1 0
#> 27.1 24.00 0 63 1 0
#> 102.1 24.00 0 49 0 0
#> 82.1 24.00 0 34 0 0
#> 162 24.00 0 51 0 0
#> 27.2 24.00 0 63 1 0
#> 193 24.00 0 45 0 1
#> 28.1 24.00 0 67 1 0
#> 191.1 24.00 0 60 0 1
#> 163 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.551 NA NA NA
#> 2 age, Cure model 0.00928 NA NA NA
#> 3 grade_ii, Cure model -0.151 NA NA NA
#> 4 grade_iii, Cure model 0.870 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00491 NA NA NA
#> 2 grade_ii, Survival model 0.489 NA NA NA
#> 3 grade_iii, Survival model 0.230 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.55120 0.00928 -0.15079 0.87036
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 251.2
#> Residual Deviance: 241.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.551196215 0.009279751 -0.150786725 0.870364664
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004906045 0.489303145 0.230328716
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.23817307 0.09599067 0.53152249 0.73401392 0.39415824 0.92835496
#> [7] 0.77227631 0.88061868 0.96151428 0.25433319 0.18945661 0.69467008
#> [13] 0.67833756 0.47477477 0.63673331 0.60239352 0.88755010 0.90809573
#> [19] 0.99362040 0.92835496 0.54964545 0.58491209 0.95492246 0.84559813
#> [25] 0.56734144 0.73401392 0.13586600 0.66198310 0.83125056 0.46488115
#> [31] 0.18945661 0.80950819 0.53152249 0.84559813 0.94166891 0.37245885
#> [37] 0.94166891 0.96151428 0.96151428 0.88755010 0.54964545 0.15616979
#> [43] 0.76456767 0.42553414 0.81682639 0.04186014 0.90809573 0.37245885
#> [49] 0.47477477 0.77994594 0.60239352 0.98084507 0.43566595 0.51299476
#> [55] 0.71064270 0.36107277 0.31312391 0.64520976 0.51299476 0.69467008
#> [61] 0.66198310 0.32679120 0.60239352 0.47477477 0.41515412 0.39415824
#> [67] 0.04186014 0.15616979 0.85963728 0.28376111 0.22173105 0.71064270
#> [73] 0.73401392 0.65362151 0.43566595 0.79487471 0.98084507 0.83845398
#> [79] 0.88755010 0.68653002 0.77994594 0.71064270 0.43566595 0.32679120
#> [85] 0.09599067 0.58491209 0.90809573 0.25433319 0.73401392 0.56734144
#> [91] 0.79487471 0.29864254 0.50337714 0.32679120 0.86666013 0.62813621
#> [97] 0.81682639 0.87364895 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000
#>
#> $Time
#> 169 86 76 100 90 145 39 43 16 194 113 181 23
#> 22.41 23.81 19.22 16.07 20.94 10.07 15.59 12.10 8.71 22.40 22.86 16.46 16.92
#> 166 134 88 10 52 91 145.1 97 8 183 154 179 100.1
#> 19.98 17.81 18.37 10.53 10.42 5.33 10.07 19.14 18.43 9.24 12.63 18.63 16.07
#> 69 45 13 150 113.1 96 76.1 154.1 101 99 101.1 16.1 16.2
#> 23.23 17.42 14.34 20.33 22.86 14.54 19.22 12.63 9.97 21.19 9.97 8.71 8.71
#> 10.1 97.1 92 26 190 57 24 52.1 36 166.1 167 88.1 149
#> 10.53 19.14 22.92 15.77 20.81 14.46 23.89 10.42 21.19 19.98 15.55 18.37 8.37
#> 68 55 188 153 197 111 55.1 181.1 45.1 139 88.2 166.2 32
#> 20.62 19.34 16.16 21.33 21.60 17.45 19.34 16.46 17.42 21.49 18.37 19.98 20.90
#> 90.1 24.1 92.1 177 66 15 188.1 100.2 30 68.1 18 149.1 60
#> 20.94 23.89 22.92 12.53 22.13 22.68 16.16 16.07 17.43 20.62 15.21 8.37 13.15
#> 10.2 171 167.1 188.2 68.2 139.1 86.1 8.1 52.2 194.1 100.3 179.1 18.1
#> 10.53 16.57 15.55 16.16 20.62 21.49 23.81 18.43 10.42 22.40 16.07 18.63 15.21
#> 136 170 139.2 42 40 57.1 56 21 165 198 109 72 31
#> 21.83 19.54 21.49 12.43 18.00 14.46 12.21 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 44 19 121 17 38 186.1 137 144 44.1 17.1 47 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 80 87 72.1 141 185 104 102 191 198.1 9 44.2 22.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 2 148 176 173 21.1 7 34 132.1 33 28 54 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 67 94 119 12 44.3 44.4 35 21.2 34.1 53 38.1 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 120 3 82 44.5 185.1 67.1 121.1 17.2 176.1 172 103 185.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.1 116 160 27.1 102.1 82.1 162 27.2 193 28.1 191.1 163 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[61]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007595313 0.278465724 0.012930742
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.105830094 0.001585044 0.020976113
#> grade_iii, Cure model
#> 0.106257346
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 192 16.44 1 31 1 0
#> 78 23.88 1 43 0 0
#> 90 20.94 1 50 0 1
#> 189 10.51 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 194 22.40 1 38 0 1
#> 63 22.77 1 31 1 0
#> 36 21.19 1 48 0 1
#> 179 18.63 1 42 0 0
#> 123 13.00 1 44 1 0
#> 37 12.52 1 57 1 0
#> 88 18.37 1 47 0 0
#> 68 20.62 1 44 0 0
#> 18 15.21 1 49 1 0
#> 133 14.65 1 57 0 0
#> 158 20.14 1 74 1 0
#> 164 23.60 1 76 0 1
#> 10 10.53 1 34 0 0
#> 24 23.89 1 38 0 0
#> 130 16.47 1 53 0 1
#> 61 10.12 1 36 0 1
#> 85 16.44 1 36 0 0
#> 111 17.45 1 47 0 1
#> 170 19.54 1 43 0 1
#> 14 12.89 1 21 0 0
#> 79 16.23 1 54 1 0
#> 25 6.32 1 34 1 0
#> 25.1 6.32 1 34 1 0
#> 42 12.43 1 49 0 1
#> 108 18.29 1 39 0 1
#> 111.1 17.45 1 47 0 1
#> 63.1 22.77 1 31 1 0
#> 170.1 19.54 1 43 0 1
#> 183 9.24 1 67 1 0
#> 188 16.16 1 46 0 1
#> 10.1 10.53 1 34 0 0
#> 123.1 13.00 1 44 1 0
#> 85.1 16.44 1 36 0 0
#> 175 21.91 1 43 0 0
#> 111.2 17.45 1 47 0 1
#> 181 16.46 1 45 0 1
#> 140 12.68 1 59 1 0
#> 29 15.45 1 68 1 0
#> 192.1 16.44 1 31 1 0
#> 125 15.65 1 67 1 0
#> 125.1 15.65 1 67 1 0
#> 183.1 9.24 1 67 1 0
#> 52 10.42 1 52 0 1
#> 114 13.68 1 NA 0 0
#> 81 14.06 1 34 0 0
#> 43 12.10 1 61 0 1
#> 155 13.08 1 26 0 0
#> 6 15.64 1 39 0 0
#> 8 18.43 1 32 0 0
#> 157 15.10 1 47 0 0
#> 195 11.76 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 100 16.07 1 60 0 0
#> 158.1 20.14 1 74 1 0
#> 117 17.46 1 26 0 1
#> 149 8.37 1 33 1 0
#> 51 18.23 1 83 0 1
#> 184 17.77 1 38 0 0
#> 56 12.21 1 60 0 0
#> 183.2 9.24 1 67 1 0
#> 76 19.22 1 54 0 1
#> 194.1 22.40 1 38 0 1
#> 86 23.81 1 58 0 1
#> 14.1 12.89 1 21 0 0
#> 188.1 16.16 1 46 0 1
#> 157.1 15.10 1 47 0 0
#> 10.2 10.53 1 34 0 0
#> 8.1 18.43 1 32 0 0
#> 128 20.35 1 35 0 1
#> 70 7.38 1 30 1 0
#> 169 22.41 1 46 0 0
#> 150 20.33 1 48 0 0
#> 13 14.34 1 54 0 1
#> 159 10.55 1 50 0 1
#> 117.1 17.46 1 26 0 1
#> 133.1 14.65 1 57 0 0
#> 40 18.00 1 28 1 0
#> 14.2 12.89 1 21 0 0
#> 14.3 12.89 1 21 0 0
#> 101 9.97 1 10 0 1
#> 8.2 18.43 1 32 0 0
#> 197 21.60 1 69 1 0
#> 187 9.92 1 39 1 0
#> 59 10.16 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 101.1 9.97 1 10 0 1
#> 29.1 15.45 1 68 1 0
#> 105 19.75 1 60 0 0
#> 153 21.33 1 55 1 0
#> 197.1 21.60 1 69 1 0
#> 100.1 16.07 1 60 0 0
#> 81.1 14.06 1 34 0 0
#> 177 12.53 1 75 0 0
#> 68.1 20.62 1 44 0 0
#> 192.2 16.44 1 31 1 0
#> 100.2 16.07 1 60 0 0
#> 30 17.43 1 78 0 0
#> 175.1 21.91 1 43 0 0
#> 140.1 12.68 1 59 1 0
#> 26 15.77 1 49 0 1
#> 97 19.14 1 65 0 1
#> 199 19.81 1 NA 0 1
#> 99 21.19 1 38 0 1
#> 59.1 10.16 1 NA 1 0
#> 158.2 20.14 1 74 1 0
#> 171 16.57 1 41 0 1
#> 93 10.33 1 52 0 1
#> 20 24.00 0 46 1 0
#> 147 24.00 0 76 1 0
#> 83 24.00 0 6 0 0
#> 198 24.00 0 66 0 1
#> 131 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 75 24.00 0 21 1 0
#> 98 24.00 0 34 1 0
#> 148 24.00 0 61 1 0
#> 98.1 24.00 0 34 1 0
#> 34 24.00 0 36 0 0
#> 198.1 24.00 0 66 0 1
#> 98.2 24.00 0 34 1 0
#> 72 24.00 0 40 0 1
#> 116 24.00 0 58 0 1
#> 172 24.00 0 41 0 0
#> 75.1 24.00 0 21 1 0
#> 19 24.00 0 57 0 1
#> 94 24.00 0 51 0 1
#> 72.1 24.00 0 40 0 1
#> 31 24.00 0 36 0 1
#> 83.1 24.00 0 6 0 0
#> 200 24.00 0 64 0 0
#> 74 24.00 0 43 0 1
#> 138 24.00 0 44 1 0
#> 83.2 24.00 0 6 0 0
#> 95 24.00 0 68 0 1
#> 28 24.00 0 67 1 0
#> 119 24.00 0 17 0 0
#> 115 24.00 0 NA 1 0
#> 35 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 176 24.00 0 43 0 1
#> 9 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 163 24.00 0 66 0 0
#> 198.2 24.00 0 66 0 1
#> 182 24.00 0 35 0 0
#> 146 24.00 0 63 1 0
#> 87 24.00 0 27 0 0
#> 152 24.00 0 36 0 1
#> 138.1 24.00 0 44 1 0
#> 119.1 24.00 0 17 0 0
#> 17 24.00 0 38 0 1
#> 19.2 24.00 0 57 0 1
#> 83.3 24.00 0 6 0 0
#> 196 24.00 0 19 0 0
#> 74.1 24.00 0 43 0 1
#> 103 24.00 0 56 1 0
#> 104 24.00 0 50 1 0
#> 47 24.00 0 38 0 1
#> 112 24.00 0 61 0 0
#> 182.1 24.00 0 35 0 0
#> 47.1 24.00 0 38 0 1
#> 28.1 24.00 0 67 1 0
#> 12 24.00 0 63 0 0
#> 115.1 24.00 0 NA 1 0
#> 165 24.00 0 47 0 0
#> 147.1 24.00 0 76 1 0
#> 54 24.00 0 53 1 0
#> 62 24.00 0 71 0 0
#> 156 24.00 0 50 1 0
#> 120 24.00 0 68 0 1
#> 17.1 24.00 0 38 0 1
#> 163.1 24.00 0 66 0 0
#> 172.1 24.00 0 41 0 0
#> 95.1 24.00 0 68 0 1
#> 21 24.00 0 47 0 0
#> 116.1 24.00 0 58 0 1
#> 64 24.00 0 43 0 0
#> 73 24.00 0 NA 0 1
#> 104.1 24.00 0 50 1 0
#> 74.2 24.00 0 43 0 1
#> 34.1 24.00 0 36 0 0
#> 80 24.00 0 41 0 0
#> 64.1 24.00 0 43 0 0
#> 143 24.00 0 51 0 0
#> 74.3 24.00 0 43 0 1
#> 28.2 24.00 0 67 1 0
#> 165.1 24.00 0 47 0 0
#> 95.2 24.00 0 68 0 1
#> 126 24.00 0 48 0 0
#> 196.1 24.00 0 19 0 0
#> 141 24.00 0 44 1 0
#> 20.1 24.00 0 46 1 0
#> 22.1 24.00 0 52 1 0
#> 22.2 24.00 0 52 1 0
#> 173 24.00 0 19 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.106 NA NA NA
#> 2 age, Cure model 0.00159 NA NA NA
#> 3 grade_ii, Cure model 0.0210 NA NA NA
#> 4 grade_iii, Cure model 0.106 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00760 NA NA NA
#> 2 grade_ii, Survival model 0.278 NA NA NA
#> 3 grade_iii, Survival model 0.0129 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.105830 0.001585 0.020976 0.106257
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.5
#> Residual Deviance: 262.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.105830094 0.001585044 0.020976113 0.106257346
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007595313 0.278465724 0.012930742
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.368360348 0.003954139 0.094648661 0.068059241 0.033054248 0.018126143
#> [7] 0.081305075 0.194232922 0.649815898 0.750716774 0.228155070 0.101733136
#> [13] 0.550839941 0.583274352 0.130990868 0.012501071 0.808904502 0.001040994
#> [19] 0.348497811 0.867886681 0.368360348 0.291643518 0.161382788 0.672168454
#> [25] 0.426090481 0.975944425 0.975944425 0.762238109 0.237038006 0.291643518
#> [31] 0.018126143 0.161382788 0.915816174 0.436195835 0.808904502 0.649815898
#> [37] 0.368360348 0.043981009 0.291643518 0.358390510 0.716559171 0.529492305
#> [43] 0.368360348 0.497748708 0.497748708 0.915816174 0.843999030 0.616325180
#> [49] 0.785450092 0.638563022 0.518800971 0.202814926 0.561638135 0.328964716
#> [55] 0.456437398 0.130990868 0.273395898 0.951718620 0.246003860 0.264219759
#> [61] 0.773812244 0.915816174 0.177418921 0.033054248 0.007804696 0.672168454
#> [67] 0.436195835 0.561638135 0.808904502 0.202814926 0.115953962 0.963835473
#> [73] 0.027544931 0.123402400 0.605196380 0.797150807 0.273395898 0.583274352
#> [79] 0.255122848 0.672168454 0.672168454 0.879894954 0.202814926 0.055733115
#> [85] 0.903787213 0.416014620 0.879894954 0.529492305 0.153375435 0.074643791
#> [91] 0.055733115 0.456437398 0.616325180 0.739220695 0.101733136 0.368360348
#> [97] 0.456437398 0.319327964 0.043981009 0.716559171 0.487201718 0.185753292
#> [103] 0.081305075 0.130990868 0.338694920 0.855916394 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 192 78 90 139 194 63 36 179 123 37 88 68 18
#> 16.44 23.88 20.94 21.49 22.40 22.77 21.19 18.63 13.00 12.52 18.37 20.62 15.21
#> 133 158 164 10 24 130 61 85 111 170 14 79 25
#> 14.65 20.14 23.60 10.53 23.89 16.47 10.12 16.44 17.45 19.54 12.89 16.23 6.32
#> 25.1 42 108 111.1 63.1 170.1 183 188 10.1 123.1 85.1 175 111.2
#> 6.32 12.43 18.29 17.45 22.77 19.54 9.24 16.16 10.53 13.00 16.44 21.91 17.45
#> 181 140 29 192.1 125 125.1 183.1 52 81 43 155 6 8
#> 16.46 12.68 15.45 16.44 15.65 15.65 9.24 10.42 14.06 12.10 13.08 15.64 18.43
#> 157 45 100 158.1 117 149 51 184 56 183.2 76 194.1 86
#> 15.10 17.42 16.07 20.14 17.46 8.37 18.23 17.77 12.21 9.24 19.22 22.40 23.81
#> 14.1 188.1 157.1 10.2 8.1 128 70 169 150 13 159 117.1 133.1
#> 12.89 16.16 15.10 10.53 18.43 20.35 7.38 22.41 20.33 14.34 10.55 17.46 14.65
#> 40 14.2 14.3 101 8.2 197 187 5 101.1 29.1 105 153 197.1
#> 18.00 12.89 12.89 9.97 18.43 21.60 9.92 16.43 9.97 15.45 19.75 21.33 21.60
#> 100.1 81.1 177 68.1 192.2 100.2 30 175.1 140.1 26 97 99 158.2
#> 16.07 14.06 12.53 20.62 16.44 16.07 17.43 21.91 12.68 15.77 19.14 21.19 20.14
#> 171 93 20 147 83 198 131 46 75 98 148 98.1 34
#> 16.57 10.33 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.1 98.2 72 116 172 75.1 19 94 72.1 31 83.1 200 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 83.2 95 28 119 35 22 176 9 19.1 163 198.2 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 87 152 138.1 119.1 17 19.2 83.3 196 74.1 103 104 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 182.1 47.1 28.1 12 165 147.1 54 62 156 120 17.1 163.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 95.1 21 116.1 64 104.1 74.2 34.1 80 64.1 143 74.3 28.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 95.2 126 196.1 141 20.1 22.1 22.2 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[62]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0007801303 0.6663512605 0.6109821108
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.49547731 0.01230676 -0.01301756
#> grade_iii, Cure model
#> 0.45814903
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 18 15.21 1 49 1 0
#> 107 11.18 1 54 1 0
#> 183 9.24 1 67 1 0
#> 136 21.83 1 43 0 1
#> 10 10.53 1 34 0 0
#> 86 23.81 1 58 0 1
#> 177 12.53 1 75 0 0
#> 168 23.72 1 70 0 0
#> 24 23.89 1 38 0 0
#> 179 18.63 1 42 0 0
#> 139 21.49 1 63 1 0
#> 30 17.43 1 78 0 0
#> 66 22.13 1 53 0 0
#> 181 16.46 1 45 0 1
#> 107.1 11.18 1 54 1 0
#> 168.1 23.72 1 70 0 0
#> 125 15.65 1 67 1 0
#> 37 12.52 1 57 1 0
#> 24.1 23.89 1 38 0 0
#> 25 6.32 1 34 1 0
#> 123 13.00 1 44 1 0
#> 101 9.97 1 10 0 1
#> 25.1 6.32 1 34 1 0
#> 171 16.57 1 41 0 1
#> 105 19.75 1 60 0 0
#> 52 10.42 1 52 0 1
#> 169 22.41 1 46 0 0
#> 166 19.98 1 48 0 0
#> 129 23.41 1 53 1 0
#> 106 16.67 1 49 1 0
#> 155 13.08 1 26 0 0
#> 51 18.23 1 83 0 1
#> 23 16.92 1 61 0 0
#> 129.1 23.41 1 53 1 0
#> 70 7.38 1 30 1 0
#> 37.1 12.52 1 57 1 0
#> 89 11.44 1 NA 0 0
#> 180 14.82 1 37 0 0
#> 197 21.60 1 69 1 0
#> 85 16.44 1 36 0 0
#> 49 12.19 1 48 1 0
#> 24.2 23.89 1 38 0 0
#> 188 16.16 1 46 0 1
#> 23.1 16.92 1 61 0 0
#> 56 12.21 1 60 0 0
#> 4 17.64 1 NA 0 1
#> 157 15.10 1 47 0 0
#> 110 17.56 1 65 0 1
#> 175 21.91 1 43 0 0
#> 170 19.54 1 43 0 1
#> 92 22.92 1 47 0 1
#> 43 12.10 1 61 0 1
#> 39 15.59 1 37 0 1
#> 171.1 16.57 1 41 0 1
#> 111 17.45 1 47 0 1
#> 30.1 17.43 1 78 0 0
#> 90 20.94 1 50 0 1
#> 68 20.62 1 44 0 0
#> 184 17.77 1 38 0 0
#> 14 12.89 1 21 0 0
#> 13 14.34 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 129.2 23.41 1 53 1 0
#> 77 7.27 1 67 0 1
#> 70.1 7.38 1 30 1 0
#> 26 15.77 1 49 0 1
#> 184.1 17.77 1 38 0 0
#> 159 10.55 1 50 0 1
#> 130 16.47 1 53 0 1
#> 32 20.90 1 37 1 0
#> 184.2 17.77 1 38 0 0
#> 15 22.68 1 48 0 0
#> 175.1 21.91 1 43 0 0
#> 60 13.15 1 38 1 0
#> 32.1 20.90 1 37 1 0
#> 58 19.34 1 39 0 0
#> 123.1 13.00 1 44 1 0
#> 91 5.33 1 61 0 1
#> 134 17.81 1 47 1 0
#> 155.1 13.08 1 26 0 0
#> 23.2 16.92 1 61 0 0
#> 190 20.81 1 42 1 0
#> 92.1 22.92 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 42 12.43 1 49 0 1
#> 187 9.92 1 39 1 0
#> 134.1 17.81 1 47 1 0
#> 15.1 22.68 1 48 0 0
#> 13.1 14.34 1 54 0 1
#> 57 14.46 1 45 0 1
#> 117 17.46 1 26 0 1
#> 167 15.55 1 56 1 0
#> 69 23.23 1 25 0 1
#> 177.1 12.53 1 75 0 0
#> 96 14.54 1 33 0 1
#> 14.1 12.89 1 21 0 0
#> 192 16.44 1 31 1 0
#> 184.3 17.77 1 38 0 0
#> 130.1 16.47 1 53 0 1
#> 78 23.88 1 43 0 0
#> 45 17.42 1 54 0 1
#> 136.1 21.83 1 43 0 1
#> 43.1 12.10 1 61 0 1
#> 13.2 14.34 1 54 0 1
#> 199 19.81 1 NA 0 1
#> 32.2 20.90 1 37 1 0
#> 150 20.33 1 48 0 0
#> 188.1 16.16 1 46 0 1
#> 133 14.65 1 57 0 0
#> 107.2 11.18 1 54 1 0
#> 26.1 15.77 1 49 0 1
#> 24.3 23.89 1 38 0 0
#> 143 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 27 24.00 0 63 1 0
#> 160.1 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 132 24.00 0 55 0 0
#> 198 24.00 0 66 0 1
#> 83 24.00 0 6 0 0
#> 131.1 24.00 0 66 0 0
#> 126 24.00 0 48 0 0
#> 120 24.00 0 68 0 1
#> 46 24.00 0 71 0 0
#> 67 24.00 0 25 0 0
#> 116 24.00 0 58 0 1
#> 98 24.00 0 34 1 0
#> 53.1 24.00 0 32 0 1
#> 152 24.00 0 36 0 1
#> 104 24.00 0 50 1 0
#> 80 24.00 0 41 0 0
#> 176 24.00 0 43 0 1
#> 104.1 24.00 0 50 1 0
#> 62 24.00 0 71 0 0
#> 148 24.00 0 61 1 0
#> 196 24.00 0 19 0 0
#> 143.1 24.00 0 51 0 0
#> 98.1 24.00 0 34 1 0
#> 146 24.00 0 63 1 0
#> 163 24.00 0 66 0 0
#> 35 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 17 24.00 0 38 0 1
#> 67.1 24.00 0 25 0 0
#> 185 24.00 0 44 1 0
#> 131.2 24.00 0 66 0 0
#> 144 24.00 0 28 0 1
#> 172 24.00 0 41 0 0
#> 48.1 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 21 24.00 0 47 0 0
#> 33 24.00 0 53 0 0
#> 7 24.00 0 37 1 0
#> 7.1 24.00 0 37 1 0
#> 1 24.00 0 23 1 0
#> 103 24.00 0 56 1 0
#> 104.2 24.00 0 50 1 0
#> 72 24.00 0 40 0 1
#> 151 24.00 0 42 0 0
#> 148.1 24.00 0 61 1 0
#> 12 24.00 0 63 0 0
#> 28 24.00 0 67 1 0
#> 71 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 196.1 24.00 0 19 0 0
#> 87 24.00 0 27 0 0
#> 34 24.00 0 36 0 0
#> 131.3 24.00 0 66 0 0
#> 64 24.00 0 43 0 0
#> 83.1 24.00 0 6 0 0
#> 20 24.00 0 46 1 0
#> 137 24.00 0 45 1 0
#> 34.1 24.00 0 36 0 0
#> 138 24.00 0 44 1 0
#> 80.1 24.00 0 41 0 0
#> 109 24.00 0 48 0 0
#> 34.2 24.00 0 36 0 0
#> 178 24.00 0 52 1 0
#> 176.1 24.00 0 43 0 1
#> 116.1 24.00 0 58 0 1
#> 80.2 24.00 0 41 0 0
#> 28.1 24.00 0 67 1 0
#> 11 24.00 0 42 0 1
#> 161 24.00 0 45 0 0
#> 84 24.00 0 39 0 1
#> 185.1 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 98.2 24.00 0 34 1 0
#> 94 24.00 0 51 0 1
#> 141 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 109.1 24.00 0 48 0 0
#> 31 24.00 0 36 0 1
#> 19.1 24.00 0 57 0 1
#> 31.1 24.00 0 36 0 1
#> 176.2 24.00 0 43 0 1
#> 44 24.00 0 56 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.495 NA NA NA
#> 2 age, Cure model 0.0123 NA NA NA
#> 3 grade_ii, Cure model -0.0130 NA NA NA
#> 4 grade_iii, Cure model 0.458 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000780 NA NA NA
#> 2 grade_ii, Survival model 0.666 NA NA NA
#> 3 grade_iii, Survival model 0.611 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.49548 0.01231 -0.01302 0.45815
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 263.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.49547731 0.01230676 -0.01301756 0.45814903
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0007801303 0.6663512605 0.6109821108
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.74450899 0.91038348 0.95909416 0.33818252 0.93484251 0.13076871
#> [7] 0.85268994 0.15060095 0.04079802 0.48706996 0.37178138 0.58232032
#> [13] 0.30195926 0.67088280 0.91038348 0.15060095 0.72302328 0.86576891
#> [19] 0.04079802 0.98268362 0.82650444 0.94703894 0.98268362 0.63966140
#> [25] 0.45913867 0.94095887 0.28968404 0.44970479 0.18719693 0.63153938
#> [31] 0.81319598 0.49631470 0.60716888 0.18719693 0.96506325 0.86576891
#> [37] 0.75855603 0.36070775 0.67856683 0.89148292 0.04079802 0.69367385
#> [43] 0.60716888 0.88506578 0.75153373 0.55685963 0.31421352 0.46856327
#> [49] 0.24146896 0.89785321 0.73025131 0.63966140 0.57394648 0.58232032
#> [55] 0.38252072 0.43081422 0.52276506 0.83959887 0.78646024 0.18719693
#> [61] 0.97682050 0.96506325 0.70848746 0.52276506 0.92872507 0.65544309
#> [67] 0.39299098 0.52276506 0.26561746 0.31421352 0.80651205 0.39299098
#> [73] 0.47781938 0.82650444 0.99423748 0.50539613 0.81319598 0.60716888
#> [79] 0.42135784 0.24146896 0.87864642 0.95308575 0.50539613 0.26561746
#> [85] 0.78646024 0.77955506 0.56545985 0.73741578 0.22780004 0.85268994
#> [91] 0.77259388 0.83959887 0.67856683 0.52276506 0.65544309 0.10770799
#> [97] 0.59891788 0.33818252 0.89785321 0.78646024 0.39299098 0.44026337
#> [103] 0.69367385 0.76557642 0.91038348 0.70848746 0.04079802 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 18 107 183 136 10 86 177 168 24 179 139 30 66
#> 15.21 11.18 9.24 21.83 10.53 23.81 12.53 23.72 23.89 18.63 21.49 17.43 22.13
#> 181 107.1 168.1 125 37 24.1 25 123 101 25.1 171 105 52
#> 16.46 11.18 23.72 15.65 12.52 23.89 6.32 13.00 9.97 6.32 16.57 19.75 10.42
#> 169 166 129 106 155 51 23 129.1 70 37.1 180 197 85
#> 22.41 19.98 23.41 16.67 13.08 18.23 16.92 23.41 7.38 12.52 14.82 21.60 16.44
#> 49 24.2 188 23.1 56 157 110 175 170 92 43 39 171.1
#> 12.19 23.89 16.16 16.92 12.21 15.10 17.56 21.91 19.54 22.92 12.10 15.59 16.57
#> 111 30.1 90 68 184 14 13 129.2 77 70.1 26 184.1 159
#> 17.45 17.43 20.94 20.62 17.77 12.89 14.34 23.41 7.27 7.38 15.77 17.77 10.55
#> 130 32 184.2 15 175.1 60 32.1 58 123.1 91 134 155.1 23.2
#> 16.47 20.90 17.77 22.68 21.91 13.15 20.90 19.34 13.00 5.33 17.81 13.08 16.92
#> 190 92.1 42 187 134.1 15.1 13.1 57 117 167 69 177.1 96
#> 20.81 22.92 12.43 9.92 17.81 22.68 14.34 14.46 17.46 15.55 23.23 12.53 14.54
#> 14.1 192 184.3 130.1 78 45 136.1 43.1 13.2 32.2 150 188.1 133
#> 12.89 16.44 17.77 16.47 23.88 17.42 21.83 12.10 14.34 20.90 20.33 16.16 14.65
#> 107.2 26.1 24.3 143 160 48 53 27 160.1 131 132 198 83
#> 11.18 15.77 23.89 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 126 120 46 67 116 98 53.1 152 104 80 176 104.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 148 196 143.1 98.1 146 163 35 47 17 67.1 185 131.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 172 48.1 174 21 33 7 7.1 1 103 104.2 72 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 12 28 71 54 196.1 87 34 131.3 64 83.1 20 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 138 80.1 109 34.2 178 176.1 116.1 80.2 28.1 11 161 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 19 98.2 94 141 122 109.1 31 19.1 31.1 176.2 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[63]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01487350 0.71037149 -0.02722386
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.395630862 0.003418382 0.403002292
#> grade_iii, Cure model
#> 1.002242311
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 29 15.45 1 68 1 0
#> 145 10.07 1 65 1 0
#> 134 17.81 1 47 1 0
#> 10 10.53 1 34 0 0
#> 52 10.42 1 52 0 1
#> 69 23.23 1 25 0 1
#> 85 16.44 1 36 0 0
#> 61 10.12 1 36 0 1
#> 59 10.16 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 76 19.22 1 54 0 1
#> 8 18.43 1 32 0 0
#> 91 5.33 1 61 0 1
#> 76.1 19.22 1 54 0 1
#> 123 13.00 1 44 1 0
#> 61.1 10.12 1 36 0 1
#> 16 8.71 1 71 0 1
#> 89 11.44 1 NA 0 0
#> 32 20.90 1 37 1 0
#> 183 9.24 1 67 1 0
#> 69.1 23.23 1 25 0 1
#> 197 21.60 1 69 1 0
#> 13 14.34 1 54 0 1
#> 170 19.54 1 43 0 1
#> 15 22.68 1 48 0 0
#> 113 22.86 1 34 0 0
#> 36 21.19 1 48 0 1
#> 29.1 15.45 1 68 1 0
#> 192 16.44 1 31 1 0
#> 114 13.68 1 NA 0 0
#> 149 8.37 1 33 1 0
#> 164 23.60 1 76 0 1
#> 184 17.77 1 38 0 0
#> 136 21.83 1 43 0 1
#> 92 22.92 1 47 0 1
#> 179 18.63 1 42 0 0
#> 149.1 8.37 1 33 1 0
#> 6 15.64 1 39 0 0
#> 108 18.29 1 39 0 1
#> 39 15.59 1 37 0 1
#> 92.1 22.92 1 47 0 1
#> 61.2 10.12 1 36 0 1
#> 15.1 22.68 1 48 0 0
#> 164.1 23.60 1 76 0 1
#> 81 14.06 1 34 0 0
#> 99 21.19 1 38 0 1
#> 128 20.35 1 35 0 1
#> 85.1 16.44 1 36 0 0
#> 24 23.89 1 38 0 0
#> 150 20.33 1 48 0 0
#> 128.1 20.35 1 35 0 1
#> 77 7.27 1 67 0 1
#> 70 7.38 1 30 1 0
#> 81.1 14.06 1 34 0 0
#> 56 12.21 1 60 0 0
#> 117 17.46 1 26 0 1
#> 133 14.65 1 57 0 0
#> 49 12.19 1 48 1 0
#> 96 14.54 1 33 0 1
#> 8.1 18.43 1 32 0 0
#> 41 18.02 1 40 1 0
#> 194 22.40 1 38 0 1
#> 145.1 10.07 1 65 1 0
#> 90 20.94 1 50 0 1
#> 190 20.81 1 42 1 0
#> 197.1 21.60 1 69 1 0
#> 190.1 20.81 1 42 1 0
#> 107 11.18 1 54 1 0
#> 117.1 17.46 1 26 0 1
#> 192.1 16.44 1 31 1 0
#> 18 15.21 1 49 1 0
#> 41.1 18.02 1 40 1 0
#> 57 14.46 1 45 0 1
#> 6.1 15.64 1 39 0 0
#> 130 16.47 1 53 0 1
#> 153 21.33 1 55 1 0
#> 195 11.76 1 NA 1 0
#> 105.1 19.75 1 60 0 0
#> 10.1 10.53 1 34 0 0
#> 36.1 21.19 1 48 0 1
#> 139 21.49 1 63 1 0
#> 58 19.34 1 39 0 0
#> 16.1 8.71 1 71 0 1
#> 199 19.81 1 NA 0 1
#> 39.1 15.59 1 37 0 1
#> 86 23.81 1 58 0 1
#> 164.2 23.60 1 76 0 1
#> 8.2 18.43 1 32 0 0
#> 93 10.33 1 52 0 1
#> 167 15.55 1 56 1 0
#> 25 6.32 1 34 1 0
#> 45 17.42 1 54 0 1
#> 164.3 23.60 1 76 0 1
#> 23 16.92 1 61 0 0
#> 49.1 12.19 1 48 1 0
#> 32.1 20.90 1 37 1 0
#> 180 14.82 1 37 0 0
#> 192.2 16.44 1 31 1 0
#> 37 12.52 1 57 1 0
#> 179.1 18.63 1 42 0 0
#> 113.1 22.86 1 34 0 0
#> 158 20.14 1 74 1 0
#> 124 9.73 1 NA 1 0
#> 170.1 19.54 1 43 0 1
#> 36.2 21.19 1 48 0 1
#> 79 16.23 1 54 1 0
#> 150.1 20.33 1 48 0 0
#> 117.2 17.46 1 26 0 1
#> 43 12.10 1 61 0 1
#> 168 23.72 1 70 0 0
#> 8.3 18.43 1 32 0 0
#> 70.1 7.38 1 30 1 0
#> 35 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 196 24.00 0 19 0 0
#> 103 24.00 0 56 1 0
#> 46 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 200 24.00 0 64 0 0
#> 54 24.00 0 53 1 0
#> 122 24.00 0 66 0 0
#> 119 24.00 0 17 0 0
#> 196.1 24.00 0 19 0 0
#> 165 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 44 24.00 0 56 0 0
#> 82 24.00 0 34 0 0
#> 121 24.00 0 57 1 0
#> 126 24.00 0 48 0 0
#> 160 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 185 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 53 24.00 0 32 0 1
#> 161.1 24.00 0 45 0 0
#> 53.1 24.00 0 32 0 1
#> 118 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 174 24.00 0 49 1 0
#> 115 24.00 0 NA 1 0
#> 75 24.00 0 21 1 0
#> 47 24.00 0 38 0 1
#> 19.1 24.00 0 57 0 1
#> 62 24.00 0 71 0 0
#> 118.1 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 162 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 72 24.00 0 40 0 1
#> 74 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 1 24.00 0 23 1 0
#> 120 24.00 0 68 0 1
#> 73 24.00 0 NA 0 1
#> 84.1 24.00 0 39 0 1
#> 138 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 98 24.00 0 34 1 0
#> 102 24.00 0 49 0 0
#> 31.1 24.00 0 36 0 1
#> 12 24.00 0 63 0 0
#> 53.2 24.00 0 32 0 1
#> 1.1 24.00 0 23 1 0
#> 151 24.00 0 42 0 0
#> 146 24.00 0 63 1 0
#> 20.1 24.00 0 46 1 0
#> 196.2 24.00 0 19 0 0
#> 82.1 24.00 0 34 0 0
#> 62.1 24.00 0 71 0 0
#> 3 24.00 0 31 1 0
#> 103.2 24.00 0 56 1 0
#> 71 24.00 0 51 0 0
#> 112.1 24.00 0 61 0 0
#> 75.1 24.00 0 21 1 0
#> 156 24.00 0 50 1 0
#> 44.1 24.00 0 56 0 0
#> 54.1 24.00 0 53 1 0
#> 74.1 24.00 0 43 0 1
#> 160.1 24.00 0 31 1 0
#> 98.1 24.00 0 34 1 0
#> 131 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 17 24.00 0 38 0 1
#> 48 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 142.1 24.00 0 53 0 0
#> 182 24.00 0 35 0 0
#> 22 24.00 0 52 1 0
#> 122.1 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 143 24.00 0 51 0 0
#> 19.2 24.00 0 57 0 1
#> 47.1 24.00 0 38 0 1
#> 126.1 24.00 0 48 0 0
#> 148 24.00 0 61 1 0
#> 191 24.00 0 60 0 1
#> 94 24.00 0 51 0 1
#> 142.2 24.00 0 53 0 0
#> 46.2 24.00 0 71 0 0
#> 7 24.00 0 37 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.396 NA NA NA
#> 2 age, Cure model 0.00342 NA NA NA
#> 3 grade_ii, Cure model 0.403 NA NA NA
#> 4 grade_iii, Cure model 1.00 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0149 NA NA NA
#> 2 grade_ii, Survival model 0.710 NA NA NA
#> 3 grade_iii, Survival model -0.0272 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.395631 0.003418 0.403002 1.002242
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 256.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.395630862 0.003418382 0.403002292 1.002242311
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01487350 0.71037149 -0.02722386
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 5.287036e-01 8.329891e-01 3.213623e-01 7.397175e-01 7.658259e-01
#> [6] 8.314720e-03 4.066720e-01 7.925388e-01 1.719627e-01 2.145076e-01
#> [11] 2.519063e-01 9.858793e-01 2.145076e-01 6.501713e-01 7.925388e-01
#> [16] 8.742436e-01 1.061921e-01 8.603814e-01 8.314720e-03 4.933999e-02
#> [21] 6.126062e-01 1.884010e-01 2.886884e-02 2.080372e-02 7.307260e-02
#> [26] 5.287036e-01 4.066720e-01 9.023330e-01 1.773578e-03 3.316541e-01
#> [31] 4.364281e-02 1.382977e-02 2.328580e-01 9.023330e-01 4.712256e-01
#> [36] 2.907071e-01 4.938727e-01 1.382977e-02 7.925388e-01 2.886884e-02
#> [41] 1.773578e-03 6.250796e-01 7.307260e-02 1.341479e-01 4.066720e-01
#> [46] 5.186885e-05 1.486909e-01 1.341479e-01 9.578355e-01 9.302094e-01
#> [51] 6.250796e-01 6.755126e-01 3.420858e-01 5.759638e-01 6.883410e-01
#> [56] 5.880683e-01 2.519063e-01 3.011010e-01 3.828640e-02 8.329891e-01
#> [61] 9.874257e-02 1.202417e-01 4.933999e-02 1.202417e-01 7.267296e-01
#> [66] 3.420858e-01 4.066720e-01 5.521487e-01 3.011010e-01 6.002743e-01
#> [71] 4.712256e-01 3.953937e-01 6.688576e-02 1.719627e-01 7.397175e-01
#> [76] 7.307260e-02 6.075714e-02 2.055687e-01 8.742436e-01 4.938727e-01
#> [81] 3.014203e-04 1.773578e-03 2.519063e-01 7.791193e-01 5.169848e-01
#> [86] 9.718804e-01 3.733783e-01 1.773578e-03 3.842920e-01 6.883410e-01
#> [91] 1.061921e-01 5.640031e-01 4.066720e-01 6.628264e-01 2.328580e-01
#> [96] 2.080372e-02 1.639984e-01 1.884010e-01 7.307260e-02 4.600031e-01
#> [101] 1.486909e-01 3.420858e-01 7.137623e-01 8.371516e-04 2.519063e-01
#> [106] 9.302094e-01 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 29 145 134 10 52 69 85 61 105 76 8 91 76.1
#> 15.45 10.07 17.81 10.53 10.42 23.23 16.44 10.12 19.75 19.22 18.43 5.33 19.22
#> 123 61.1 16 32 183 69.1 197 13 170 15 113 36 29.1
#> 13.00 10.12 8.71 20.90 9.24 23.23 21.60 14.34 19.54 22.68 22.86 21.19 15.45
#> 192 149 164 184 136 92 179 149.1 6 108 39 92.1 61.2
#> 16.44 8.37 23.60 17.77 21.83 22.92 18.63 8.37 15.64 18.29 15.59 22.92 10.12
#> 15.1 164.1 81 99 128 85.1 24 150 128.1 77 70 81.1 56
#> 22.68 23.60 14.06 21.19 20.35 16.44 23.89 20.33 20.35 7.27 7.38 14.06 12.21
#> 117 133 49 96 8.1 41 194 145.1 90 190 197.1 190.1 107
#> 17.46 14.65 12.19 14.54 18.43 18.02 22.40 10.07 20.94 20.81 21.60 20.81 11.18
#> 117.1 192.1 18 41.1 57 6.1 130 153 105.1 10.1 36.1 139 58
#> 17.46 16.44 15.21 18.02 14.46 15.64 16.47 21.33 19.75 10.53 21.19 21.49 19.34
#> 16.1 39.1 86 164.2 8.2 93 167 25 45 164.3 23 49.1 32.1
#> 8.71 15.59 23.81 23.60 18.43 10.33 15.55 6.32 17.42 23.60 16.92 12.19 20.90
#> 180 192.2 37 179.1 113.1 158 170.1 36.2 79 150.1 117.2 43 168
#> 14.82 16.44 12.52 18.63 22.86 20.14 19.54 21.19 16.23 20.33 17.46 12.10 23.72
#> 8.3 70.1 35 19 196 103 46 31 200 54 122 119 196.1
#> 18.43 7.38 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 84 44 82 121 126 160 161 185 176 53 161.1 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 46.1 174 75 47 19.1 62 118.1 20 162 64 72 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 1 120 84.1 138 103.1 98 102 31.1 12 53.2 1.1 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 20.1 196.2 82.1 62.1 3 103.2 71 112.1 75.1 156 44.1 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 160.1 98.1 131 142 17 48 172 142.1 182 22 122.1 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 19.2 47.1 126.1 148 191 94 142.2 46.2 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[64]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00509996 0.10012264 -0.12397963
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.647161189 0.008733458 0.122997043
#> grade_iii, Cure model
#> 1.157257415
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 177 12.53 1 75 0 0
#> 188 16.16 1 46 0 1
#> 197 21.60 1 69 1 0
#> 129 23.41 1 53 1 0
#> 123 13.00 1 44 1 0
#> 69 23.23 1 25 0 1
#> 18 15.21 1 49 1 0
#> 136 21.83 1 43 0 1
#> 60 13.15 1 38 1 0
#> 189 10.51 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 52 10.42 1 52 0 1
#> 56 12.21 1 60 0 0
#> 188.1 16.16 1 46 0 1
#> 29 15.45 1 68 1 0
#> 110 17.56 1 65 0 1
#> 158 20.14 1 74 1 0
#> 139 21.49 1 63 1 0
#> 70 7.38 1 30 1 0
#> 81 14.06 1 34 0 0
#> 42 12.43 1 49 0 1
#> 4 17.64 1 NA 0 1
#> 150 20.33 1 48 0 0
#> 37 12.52 1 57 1 0
#> 14 12.89 1 21 0 0
#> 4.1 17.64 1 NA 0 1
#> 105 19.75 1 60 0 0
#> 60.1 13.15 1 38 1 0
#> 157 15.10 1 47 0 0
#> 81.1 14.06 1 34 0 0
#> 97.1 19.14 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 36 21.19 1 48 0 1
#> 10 10.53 1 34 0 0
#> 32 20.90 1 37 1 0
#> 10.1 10.53 1 34 0 0
#> 93 10.33 1 52 0 1
#> 10.2 10.53 1 34 0 0
#> 10.3 10.53 1 34 0 0
#> 106 16.67 1 49 1 0
#> 90 20.94 1 50 0 1
#> 106.1 16.67 1 49 1 0
#> 134 17.81 1 47 1 0
#> 180 14.82 1 37 0 0
#> 10.4 10.53 1 34 0 0
#> 153 21.33 1 55 1 0
#> 89 11.44 1 NA 0 0
#> 175 21.91 1 43 0 0
#> 188.2 16.16 1 46 0 1
#> 154 12.63 1 20 1 0
#> 36.1 21.19 1 48 0 1
#> 145 10.07 1 65 1 0
#> 57 14.46 1 45 0 1
#> 42.1 12.43 1 49 0 1
#> 124 9.73 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 24 23.89 1 38 0 0
#> 91.1 5.33 1 61 0 1
#> 168 23.72 1 70 0 0
#> 69.1 23.23 1 25 0 1
#> 43 12.10 1 61 0 1
#> 15 22.68 1 48 0 0
#> 139.1 21.49 1 63 1 0
#> 177.1 12.53 1 75 0 0
#> 127 3.53 1 62 0 1
#> 97.2 19.14 1 65 0 1
#> 40 18.00 1 28 1 0
#> 97.3 19.14 1 65 0 1
#> 29.1 15.45 1 68 1 0
#> 51 18.23 1 83 0 1
#> 92 22.92 1 47 0 1
#> 139.2 21.49 1 63 1 0
#> 167 15.55 1 56 1 0
#> 153.1 21.33 1 55 1 0
#> 114 13.68 1 NA 0 0
#> 14.1 12.89 1 21 0 0
#> 89.1 11.44 1 NA 0 0
#> 194 22.40 1 38 0 1
#> 92.1 22.92 1 47 0 1
#> 189.1 10.51 1 NA 1 0
#> 32.1 20.90 1 37 1 0
#> 166 19.98 1 48 0 0
#> 129.1 23.41 1 53 1 0
#> 123.1 13.00 1 44 1 0
#> 93.1 10.33 1 52 0 1
#> 59 10.16 1 NA 1 0
#> 134.1 17.81 1 47 1 0
#> 128 20.35 1 35 0 1
#> 55 19.34 1 69 0 1
#> 155 13.08 1 26 0 0
#> 183 9.24 1 67 1 0
#> 189.2 10.51 1 NA 1 0
#> 197.1 21.60 1 69 1 0
#> 69.2 23.23 1 25 0 1
#> 36.2 21.19 1 48 0 1
#> 101 9.97 1 10 0 1
#> 180.1 14.82 1 37 0 0
#> 166.1 19.98 1 48 0 0
#> 24.1 23.89 1 38 0 0
#> 68 20.62 1 44 0 0
#> 133 14.65 1 57 0 0
#> 111 17.45 1 47 0 1
#> 14.2 12.89 1 21 0 0
#> 136.1 21.83 1 43 0 1
#> 149 8.37 1 33 1 0
#> 86 23.81 1 58 0 1
#> 6 15.64 1 39 0 0
#> 42.2 12.43 1 49 0 1
#> 111.1 17.45 1 47 0 1
#> 105.1 19.75 1 60 0 0
#> 136.2 21.83 1 43 0 1
#> 162 24.00 0 51 0 0
#> 53 24.00 0 32 0 1
#> 104 24.00 0 50 1 0
#> 82 24.00 0 34 0 0
#> 173 24.00 0 19 0 1
#> 1 24.00 0 23 1 0
#> 122 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 143.1 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 21 24.00 0 47 0 0
#> 33 24.00 0 53 0 0
#> 122.1 24.00 0 66 0 0
#> 196 24.00 0 19 0 0
#> 46 24.00 0 71 0 0
#> 163 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 3 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 1.1 24.00 0 23 1 0
#> 176 24.00 0 43 0 1
#> 28 24.00 0 67 1 0
#> 178 24.00 0 52 1 0
#> 46.1 24.00 0 71 0 0
#> 22 24.00 0 52 1 0
#> 104.1 24.00 0 50 1 0
#> 54 24.00 0 53 1 0
#> 21.1 24.00 0 47 0 0
#> 34 24.00 0 36 0 0
#> 173.1 24.00 0 19 0 1
#> 176.1 24.00 0 43 0 1
#> 174 24.00 0 49 1 0
#> 38.1 24.00 0 31 1 0
#> 46.2 24.00 0 71 0 0
#> 131 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 46.3 24.00 0 71 0 0
#> 67 24.00 0 25 0 0
#> 148 24.00 0 61 1 0
#> 11 24.00 0 42 0 1
#> 54.1 24.00 0 53 1 0
#> 17.1 24.00 0 38 0 1
#> 46.4 24.00 0 71 0 0
#> 94 24.00 0 51 0 1
#> 200 24.00 0 64 0 0
#> 147 24.00 0 76 1 0
#> 87 24.00 0 27 0 0
#> 83 24.00 0 6 0 0
#> 121 24.00 0 57 1 0
#> 126 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 64 24.00 0 43 0 0
#> 21.2 24.00 0 47 0 0
#> 193.1 24.00 0 45 0 1
#> 38.2 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 64.1 24.00 0 43 0 0
#> 193.2 24.00 0 45 0 1
#> 126.1 24.00 0 48 0 0
#> 48 24.00 0 31 1 0
#> 156.1 24.00 0 50 1 0
#> 152 24.00 0 36 0 1
#> 173.2 24.00 0 19 0 1
#> 151 24.00 0 42 0 0
#> 147.1 24.00 0 76 1 0
#> 72 24.00 0 40 0 1
#> 118.1 24.00 0 44 1 0
#> 178.1 24.00 0 52 1 0
#> 64.2 24.00 0 43 0 0
#> 142 24.00 0 53 0 0
#> 126.2 24.00 0 48 0 0
#> 71 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 147.2 24.00 0 76 1 0
#> 151.1 24.00 0 42 0 0
#> 35 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 28.1 24.00 0 67 1 0
#> 178.2 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 172 24.00 0 41 0 0
#> 48.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.647 NA NA NA
#> 2 age, Cure model 0.00873 NA NA NA
#> 3 grade_ii, Cure model 0.123 NA NA NA
#> 4 grade_iii, Cure model 1.16 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00510 NA NA NA
#> 2 grade_ii, Survival model 0.100 NA NA NA
#> 3 grade_iii, Survival model -0.124 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.647161 0.008733 0.122997 1.157257
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 261.1
#> Residual Deviance: 249.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.647161189 0.008733458 0.122997043 1.157257415
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00509996 0.10012264 -0.12397963
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.707462501 0.436137353 0.110364733 0.024585347 0.638058159 0.035878448
#> [7] 0.512666198 0.088309579 0.603469809 0.302804596 0.862327700 0.778396652
#> [13] 0.436137353 0.490515840 0.383181607 0.245938065 0.126093543 0.949490705
#> [19] 0.580578225 0.742821518 0.236657282 0.730949013 0.661181697 0.273986303
#> [25] 0.603469809 0.523897795 0.580578225 0.302804596 0.018628522 0.166345850
#> [31] 0.802648459 0.200661302 0.802648459 0.874665034 0.802648459 0.802648459
#> [37] 0.414852751 0.191682769 0.414852751 0.362600459 0.535180954 0.802648459
#> [43] 0.149796787 0.080848128 0.436137353 0.695744849 0.166345850 0.899388982
#> [49] 0.569090221 0.742821518 0.962058114 0.002570631 0.962058114 0.013354755
#> [55] 0.035878448 0.790489744 0.066386324 0.126093543 0.707462501 0.987259548
#> [61] 0.302804596 0.352237466 0.302804596 0.490515840 0.341887215 0.053176859
#> [67] 0.126093543 0.479423569 0.149796787 0.661181697 0.073520231 0.053176859
#> [73] 0.200661302 0.255304471 0.024585347 0.638058159 0.874665034 0.362600459
#> [79] 0.227454895 0.293010461 0.626439403 0.924384102 0.110364733 0.035878448
#> [85] 0.166345850 0.911872793 0.535180954 0.255304471 0.002570631 0.218348708
#> [91] 0.557670861 0.393719176 0.661181697 0.088309579 0.936931860 0.008653840
#> [97] 0.468374585 0.742821518 0.393719176 0.273986303 0.088309579 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 177 188 197 129 123 69 18 136 60 97 52 56 188.1
#> 12.53 16.16 21.60 23.41 13.00 23.23 15.21 21.83 13.15 19.14 10.42 12.21 16.16
#> 29 110 158 139 70 81 42 150 37 14 105 60.1 157
#> 15.45 17.56 20.14 21.49 7.38 14.06 12.43 20.33 12.52 12.89 19.75 13.15 15.10
#> 81.1 97.1 164 36 10 32 10.1 93 10.2 10.3 106 90 106.1
#> 14.06 19.14 23.60 21.19 10.53 20.90 10.53 10.33 10.53 10.53 16.67 20.94 16.67
#> 134 180 10.4 153 175 188.2 154 36.1 145 57 42.1 91 24
#> 17.81 14.82 10.53 21.33 21.91 16.16 12.63 21.19 10.07 14.46 12.43 5.33 23.89
#> 91.1 168 69.1 43 15 139.1 177.1 127 97.2 40 97.3 29.1 51
#> 5.33 23.72 23.23 12.10 22.68 21.49 12.53 3.53 19.14 18.00 19.14 15.45 18.23
#> 92 139.2 167 153.1 14.1 194 92.1 32.1 166 129.1 123.1 93.1 134.1
#> 22.92 21.49 15.55 21.33 12.89 22.40 22.92 20.90 19.98 23.41 13.00 10.33 17.81
#> 128 55 155 183 197.1 69.2 36.2 101 180.1 166.1 24.1 68 133
#> 20.35 19.34 13.08 9.24 21.60 23.23 21.19 9.97 14.82 19.98 23.89 20.62 14.65
#> 111 14.2 136.1 149 86 6 42.2 111.1 105.1 136.2 162 53 104
#> 17.45 12.89 21.83 8.37 23.81 15.64 12.43 17.45 19.75 21.83 24.00 24.00 24.00
#> 82 173 1 122 143 17 143.1 38 132 21 33 122.1 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 163 62 3 193 1.1 176 28 178 46.1 22 104.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.1 34 173.1 176.1 174 38.1 46.2 131 118 156 46.3 67 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 54.1 17.1 46.4 94 200 147 87 83 121 126 141 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 21.2 193.1 38.2 137 65 64.1 193.2 126.1 48 156.1 152 173.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 147.1 72 118.1 178.1 64.2 142 126.2 71 182 147.2 151.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 191 28.1 178.2 20 172 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[65]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01111873 0.40802327 0.16647382
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.19413292 0.02382549 0.02594392
#> grade_iii, Cure model
#> 0.66327562
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 90 20.94 1 50 0 1
#> 149 8.37 1 33 1 0
#> 10 10.53 1 34 0 0
#> 86 23.81 1 58 0 1
#> 195 11.76 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 134 17.81 1 47 1 0
#> 157 15.10 1 47 0 0
#> 168 23.72 1 70 0 0
#> 195.1 11.76 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 134.1 17.81 1 47 1 0
#> 55 19.34 1 69 0 1
#> 189 10.51 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 183 9.24 1 67 1 0
#> 30 17.43 1 78 0 0
#> 184 17.77 1 38 0 0
#> 4 17.64 1 NA 0 1
#> 124 9.73 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 107 11.18 1 54 1 0
#> 90.1 20.94 1 50 0 1
#> 110 17.56 1 65 0 1
#> 105 19.75 1 60 0 0
#> 93 10.33 1 52 0 1
#> 123 13.00 1 44 1 0
#> 55.1 19.34 1 69 0 1
#> 30.1 17.43 1 78 0 0
#> 110.1 17.56 1 65 0 1
#> 164 23.60 1 76 0 1
#> 197 21.60 1 69 1 0
#> 111 17.45 1 47 0 1
#> 5 16.43 1 51 0 1
#> 139 21.49 1 63 1 0
#> 192.1 16.44 1 31 1 0
#> 68 20.62 1 44 0 0
#> 49 12.19 1 48 1 0
#> 86.1 23.81 1 58 0 1
#> 110.2 17.56 1 65 0 1
#> 49.1 12.19 1 48 1 0
#> 101 9.97 1 10 0 1
#> 40 18.00 1 28 1 0
#> 18 15.21 1 49 1 0
#> 68.1 20.62 1 44 0 0
#> 55.2 19.34 1 69 0 1
#> 76 19.22 1 54 0 1
#> 129 23.41 1 53 1 0
#> 78 23.88 1 43 0 0
#> 194 22.40 1 38 0 1
#> 157.1 15.10 1 47 0 0
#> 15 22.68 1 48 0 0
#> 180 14.82 1 37 0 0
#> 157.2 15.10 1 47 0 0
#> 55.3 19.34 1 69 0 1
#> 117 17.46 1 26 0 1
#> 52 10.42 1 52 0 1
#> 133 14.65 1 57 0 0
#> 136 21.83 1 43 0 1
#> 24 23.89 1 38 0 0
#> 45 17.42 1 54 0 1
#> 81 14.06 1 34 0 0
#> 41 18.02 1 40 1 0
#> 29 15.45 1 68 1 0
#> 78.1 23.88 1 43 0 0
#> 88 18.37 1 47 0 0
#> 129.1 23.41 1 53 1 0
#> 129.2 23.41 1 53 1 0
#> 111.1 17.45 1 47 0 1
#> 97 19.14 1 65 0 1
#> 164.1 23.60 1 76 0 1
#> 177 12.53 1 75 0 0
#> 134.2 17.81 1 47 1 0
#> 68.2 20.62 1 44 0 0
#> 96 14.54 1 33 0 1
#> 158 20.14 1 74 1 0
#> 110.3 17.56 1 65 0 1
#> 117.1 17.46 1 26 0 1
#> 13 14.34 1 54 0 1
#> 81.1 14.06 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 76.1 19.22 1 54 0 1
#> 26 15.77 1 49 0 1
#> 23 16.92 1 61 0 0
#> 42 12.43 1 49 0 1
#> 155 13.08 1 26 0 0
#> 149.1 8.37 1 33 1 0
#> 40.1 18.00 1 28 1 0
#> 145 10.07 1 65 1 0
#> 76.2 19.22 1 54 0 1
#> 100 16.07 1 60 0 0
#> 68.3 20.62 1 44 0 0
#> 123.1 13.00 1 44 1 0
#> 39 15.59 1 37 0 1
#> 139.1 21.49 1 63 1 0
#> 177.1 12.53 1 75 0 0
#> 167 15.55 1 56 1 0
#> 110.4 17.56 1 65 0 1
#> 55.4 19.34 1 69 0 1
#> 158.1 20.14 1 74 1 0
#> 8 18.43 1 32 0 0
#> 63 22.77 1 31 1 0
#> 60 13.15 1 38 1 0
#> 171 16.57 1 41 0 1
#> 99 21.19 1 38 0 1
#> 49.2 12.19 1 48 1 0
#> 55.5 19.34 1 69 0 1
#> 89 11.44 1 NA 0 0
#> 128.1 20.35 1 35 0 1
#> 155.1 13.08 1 26 0 0
#> 86.2 23.81 1 58 0 1
#> 195.2 11.76 1 NA 1 0
#> 120 24.00 0 68 0 1
#> 142 24.00 0 53 0 0
#> 161 24.00 0 45 0 0
#> 95 24.00 0 68 0 1
#> 21 24.00 0 47 0 0
#> 174 24.00 0 49 1 0
#> 27 24.00 0 63 1 0
#> 162 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 193 24.00 0 45 0 1
#> 98 24.00 0 34 1 0
#> 161.1 24.00 0 45 0 0
#> 83 24.00 0 6 0 0
#> 48 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 46 24.00 0 71 0 0
#> 34 24.00 0 36 0 0
#> 98.1 24.00 0 34 1 0
#> 48.1 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 161.2 24.00 0 45 0 0
#> 160.1 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 35 24.00 0 51 0 0
#> 198 24.00 0 66 0 1
#> 28 24.00 0 67 1 0
#> 54 24.00 0 53 1 0
#> 75 24.00 0 21 1 0
#> 2.1 24.00 0 9 0 0
#> 162.1 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 11 24.00 0 42 0 1
#> 119 24.00 0 17 0 0
#> 144 24.00 0 28 0 1
#> 138 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 9 24.00 0 31 1 0
#> 112.1 24.00 0 61 0 0
#> 126 24.00 0 48 0 0
#> 98.2 24.00 0 34 1 0
#> 172 24.00 0 41 0 0
#> 21.1 24.00 0 47 0 0
#> 95.1 24.00 0 68 0 1
#> 165 24.00 0 47 0 0
#> 147 24.00 0 76 1 0
#> 34.1 24.00 0 36 0 0
#> 120.1 24.00 0 68 0 1
#> 160.2 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 163 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 163.1 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 31.1 24.00 0 36 0 1
#> 160.3 24.00 0 31 1 0
#> 21.2 24.00 0 47 0 0
#> 67 24.00 0 25 0 0
#> 121 24.00 0 57 1 0
#> 65 24.00 0 57 1 0
#> 28.1 24.00 0 67 1 0
#> 160.4 24.00 0 31 1 0
#> 137.1 24.00 0 45 1 0
#> 182 24.00 0 35 0 0
#> 172.1 24.00 0 41 0 0
#> 126.1 24.00 0 48 0 0
#> 31.2 24.00 0 36 0 1
#> 12 24.00 0 63 0 0
#> 3 24.00 0 31 1 0
#> 1.1 24.00 0 23 1 0
#> 74 24.00 0 43 0 1
#> 119.1 24.00 0 17 0 0
#> 178 24.00 0 52 1 0
#> 174.1 24.00 0 49 1 0
#> 102 24.00 0 49 0 0
#> 174.2 24.00 0 49 1 0
#> 121.1 24.00 0 57 1 0
#> 11.1 24.00 0 42 0 1
#> 156 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 144.1 24.00 0 28 0 1
#> 19 24.00 0 57 0 1
#> 174.3 24.00 0 49 1 0
#> 53 24.00 0 32 0 1
#> 198.1 24.00 0 66 0 1
#> 74.1 24.00 0 43 0 1
#> 11.2 24.00 0 42 0 1
#> 193.1 24.00 0 45 0 1
#> 116 24.00 0 58 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.19 NA NA NA
#> 2 age, Cure model 0.0238 NA NA NA
#> 3 grade_ii, Cure model 0.0259 NA NA NA
#> 4 grade_iii, Cure model 0.663 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0111 NA NA NA
#> 2 grade_ii, Survival model 0.408 NA NA NA
#> 3 grade_iii, Survival model 0.166 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.19413 0.02383 0.02594 0.66328
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 253.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.19413292 0.02382549 0.02594392 0.66327562
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01111873 0.40802327 0.16647382
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.102941579 0.959842540 0.879785931 0.007609473 0.510873338 0.322190839
#> [7] 0.615607105 0.016918560 0.145432635 0.322190839 0.185103011 0.986503462
#> [13] 0.946402451 0.454671925 0.351338201 0.057774379 0.866636232 0.102941579
#> [19] 0.361434797 0.176765100 0.906275960 0.763772479 0.185103011 0.454671925
#> [25] 0.361434797 0.021450054 0.076456788 0.433194842 0.533471101 0.082994893
#> [31] 0.510873338 0.116824387 0.827884024 0.007609473 0.361434797 0.827884024
#> [37] 0.933016740 0.302649361 0.603710132 0.116824387 0.185103011 0.235341816
#> [43] 0.031445196 0.002648938 0.063861712 0.615607105 0.051933765 0.651442430
#> [49] 0.615607105 0.185103011 0.412032252 0.892997796 0.663690704 0.070083364
#> [55] 0.000576010 0.476753971 0.700918032 0.292649180 0.591843064 0.002648938
#> [61] 0.282661338 0.031445196 0.031445196 0.433194842 0.263074187 0.021450054
#> [67] 0.789069159 0.322190839 0.116824387 0.676046014 0.160839510 0.361434797
#> [73] 0.412032252 0.688442479 0.700918032 0.235341816 0.556595375 0.488018831
#> [79] 0.814833077 0.738541044 0.959842540 0.302649361 0.919620107 0.235341816
#> [85] 0.544973529 0.116824387 0.763772479 0.568294175 0.082994893 0.789069159
#> [91] 0.580045533 0.361434797 0.185103011 0.160839510 0.272815123 0.046353085
#> [97] 0.725924884 0.499413229 0.096060423 0.827884024 0.185103011 0.145432635
#> [103] 0.738541044 0.007609473 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 90 149 10 86 192 134 157 168 128 134.1 55 127 183
#> 20.94 8.37 10.53 23.81 16.44 17.81 15.10 23.72 20.35 17.81 19.34 3.53 9.24
#> 30 184 169 107 90.1 110 105 93 123 55.1 30.1 110.1 164
#> 17.43 17.77 22.41 11.18 20.94 17.56 19.75 10.33 13.00 19.34 17.43 17.56 23.60
#> 197 111 5 139 192.1 68 49 86.1 110.2 49.1 101 40 18
#> 21.60 17.45 16.43 21.49 16.44 20.62 12.19 23.81 17.56 12.19 9.97 18.00 15.21
#> 68.1 55.2 76 129 78 194 157.1 15 180 157.2 55.3 117 52
#> 20.62 19.34 19.22 23.41 23.88 22.40 15.10 22.68 14.82 15.10 19.34 17.46 10.42
#> 133 136 24 45 81 41 29 78.1 88 129.1 129.2 111.1 97
#> 14.65 21.83 23.89 17.42 14.06 18.02 15.45 23.88 18.37 23.41 23.41 17.45 19.14
#> 164.1 177 134.2 68.2 96 158 110.3 117.1 13 81.1 76.1 26 23
#> 23.60 12.53 17.81 20.62 14.54 20.14 17.56 17.46 14.34 14.06 19.22 15.77 16.92
#> 42 155 149.1 40.1 145 76.2 100 68.3 123.1 39 139.1 177.1 167
#> 12.43 13.08 8.37 18.00 10.07 19.22 16.07 20.62 13.00 15.59 21.49 12.53 15.55
#> 110.4 55.4 158.1 8 63 60 171 99 49.2 55.5 128.1 155.1 86.2
#> 17.56 19.34 20.14 18.43 22.77 13.15 16.57 21.19 12.19 19.34 20.35 13.08 23.81
#> 120 142 161 95 21 174 27 162 112 193 98 161.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 31 46 34 98.1 48.1 160 161.2 160.1 2 35 198 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 75 2.1 162.1 109 11 119 144 138 132 9 112.1 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.2 172 21.1 95.1 165 147 34.1 120.1 160.2 47 163 137 163.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 31.1 160.3 21.2 67 121 65 28.1 160.4 137.1 182 172.1 126.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.2 12 3 1.1 74 119.1 178 174.1 102 174.2 121.1 11.1 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 144.1 19 174.3 53 198.1 74.1 11.2 193.1 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[66]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01190674 0.29038822 0.13341740
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.075880191 -0.001547522 -0.058433224
#> grade_iii, Cure model
#> 0.644974161
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 158 20.14 1 74 1 0
#> 45 17.42 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 154 12.63 1 20 1 0
#> 183 9.24 1 67 1 0
#> 79 16.23 1 54 1 0
#> 10 10.53 1 34 0 0
#> 108 18.29 1 39 0 1
#> 29 15.45 1 68 1 0
#> 194 22.40 1 38 0 1
#> 170 19.54 1 43 0 1
#> 134 17.81 1 47 1 0
#> 194.1 22.40 1 38 0 1
#> 105 19.75 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 179 18.63 1 42 0 0
#> 129 23.41 1 53 1 0
#> 70 7.38 1 30 1 0
#> 134.1 17.81 1 47 1 0
#> 90 20.94 1 50 0 1
#> 155 13.08 1 26 0 0
#> 30 17.43 1 78 0 0
#> 164 23.60 1 76 0 1
#> 158.1 20.14 1 74 1 0
#> 134.2 17.81 1 47 1 0
#> 41 18.02 1 40 1 0
#> 192 16.44 1 31 1 0
#> 107 11.18 1 54 1 0
#> 166 19.98 1 48 0 0
#> 158.2 20.14 1 74 1 0
#> 171 16.57 1 41 0 1
#> 168 23.72 1 70 0 0
#> 57 14.46 1 45 0 1
#> 32 20.90 1 37 1 0
#> 58 19.34 1 39 0 0
#> 6.1 15.64 1 39 0 0
#> 30.1 17.43 1 78 0 0
#> 199 19.81 1 NA 0 1
#> 183.1 9.24 1 67 1 0
#> 150 20.33 1 48 0 0
#> 57.1 14.46 1 45 0 1
#> 49 12.19 1 48 1 0
#> 150.1 20.33 1 48 0 0
#> 179.1 18.63 1 42 0 0
#> 59 10.16 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 108.1 18.29 1 39 0 1
#> 32.1 20.90 1 37 1 0
#> 26 15.77 1 49 0 1
#> 15 22.68 1 48 0 0
#> 184 17.77 1 38 0 0
#> 25 6.32 1 34 1 0
#> 8 18.43 1 32 0 0
#> 58.1 19.34 1 39 0 0
#> 188 16.16 1 46 0 1
#> 18 15.21 1 49 1 0
#> 90.1 20.94 1 50 0 1
#> 99 21.19 1 38 0 1
#> 128 20.35 1 35 0 1
#> 140 12.68 1 59 1 0
#> 140.1 12.68 1 59 1 0
#> 106 16.67 1 49 1 0
#> 169 22.41 1 46 0 0
#> 57.2 14.46 1 45 0 1
#> 57.3 14.46 1 45 0 1
#> 177 12.53 1 75 0 0
#> 40 18.00 1 28 1 0
#> 13 14.34 1 54 0 1
#> 136 21.83 1 43 0 1
#> 43 12.10 1 61 0 1
#> 57.4 14.46 1 45 0 1
#> 129.1 23.41 1 53 1 0
#> 45.1 17.42 1 54 0 1
#> 158.3 20.14 1 74 1 0
#> 130 16.47 1 53 0 1
#> 171.1 16.57 1 41 0 1
#> 26.1 15.77 1 49 0 1
#> 99.1 21.19 1 38 0 1
#> 40.1 18.00 1 28 1 0
#> 130.1 16.47 1 53 0 1
#> 105.1 19.75 1 60 0 0
#> 187 9.92 1 39 1 0
#> 108.2 18.29 1 39 0 1
#> 155.1 13.08 1 26 0 0
#> 10.1 10.53 1 34 0 0
#> 66 22.13 1 53 0 0
#> 6.2 15.64 1 39 0 0
#> 139 21.49 1 63 1 0
#> 57.5 14.46 1 45 0 1
#> 91 5.33 1 61 0 1
#> 79.1 16.23 1 54 1 0
#> 107.1 11.18 1 54 1 0
#> 89 11.44 1 NA 0 0
#> 171.2 16.57 1 41 0 1
#> 45.2 17.42 1 54 0 1
#> 192.1 16.44 1 31 1 0
#> 61 10.12 1 36 0 1
#> 130.2 16.47 1 53 0 1
#> 93 10.33 1 52 0 1
#> 16 8.71 1 71 0 1
#> 58.2 19.34 1 39 0 0
#> 127 3.53 1 62 0 1
#> 199.1 19.81 1 NA 0 1
#> 36 21.19 1 48 0 1
#> 107.2 11.18 1 54 1 0
#> 57.6 14.46 1 45 0 1
#> 6.3 15.64 1 39 0 0
#> 108.3 18.29 1 39 0 1
#> 6.4 15.64 1 39 0 0
#> 133 14.65 1 57 0 0
#> 57.7 14.46 1 45 0 1
#> 94 24.00 0 51 0 1
#> 53 24.00 0 32 0 1
#> 74 24.00 0 43 0 1
#> 38 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 178 24.00 0 52 1 0
#> 132 24.00 0 55 0 0
#> 67 24.00 0 25 0 0
#> 98 24.00 0 34 1 0
#> 62 24.00 0 71 0 0
#> 103 24.00 0 56 1 0
#> 12 24.00 0 63 0 0
#> 185 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 178.1 24.00 0 52 1 0
#> 2 24.00 0 9 0 0
#> 9 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 143 24.00 0 51 0 0
#> 141 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 64 24.00 0 43 0 0
#> 132.1 24.00 0 55 0 0
#> 160 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 144 24.00 0 28 0 1
#> 178.2 24.00 0 52 1 0
#> 191.1 24.00 0 60 0 1
#> 34 24.00 0 36 0 0
#> 147 24.00 0 76 1 0
#> 121 24.00 0 57 1 0
#> 95 24.00 0 68 0 1
#> 20 24.00 0 46 1 0
#> 137 24.00 0 45 1 0
#> 34.1 24.00 0 36 0 0
#> 67.1 24.00 0 25 0 0
#> 27 24.00 0 63 1 0
#> 144.1 24.00 0 28 0 1
#> 120 24.00 0 68 0 1
#> 137.1 24.00 0 45 1 0
#> 64.1 24.00 0 43 0 0
#> 87 24.00 0 27 0 0
#> 12.1 24.00 0 63 0 0
#> 1.1 24.00 0 23 1 0
#> 152 24.00 0 36 0 1
#> 161 24.00 0 45 0 0
#> 178.3 24.00 0 52 1 0
#> 160.1 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 38.1 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 65 24.00 0 57 1 0
#> 71 24.00 0 51 0 0
#> 95.1 24.00 0 68 0 1
#> 46 24.00 0 71 0 0
#> 191.2 24.00 0 60 0 1
#> 131 24.00 0 66 0 0
#> 156.1 24.00 0 50 1 0
#> 176.1 24.00 0 43 0 1
#> 84 24.00 0 39 0 1
#> 46.1 24.00 0 71 0 0
#> 27.1 24.00 0 63 1 0
#> 122.1 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 198 24.00 0 66 0 1
#> 147.1 24.00 0 76 1 0
#> 33 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 75 24.00 0 21 1 0
#> 198.1 24.00 0 66 0 1
#> 148.1 24.00 0 61 1 0
#> 98.1 24.00 0 34 1 0
#> 193 24.00 0 45 0 1
#> 94.1 24.00 0 51 0 1
#> 98.2 24.00 0 34 1 0
#> 33.1 24.00 0 53 0 0
#> 131.1 24.00 0 66 0 0
#> 31 24.00 0 36 0 1
#> 65.1 24.00 0 57 1 0
#> 62.1 24.00 0 71 0 0
#> 84.1 24.00 0 39 0 1
#> 27.2 24.00 0 63 1 0
#> 163 24.00 0 66 0 0
#> 178.4 24.00 0 52 1 0
#> 80.1 24.00 0 41 0 0
#> 9.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0759 NA NA NA
#> 2 age, Cure model -0.00155 NA NA NA
#> 3 grade_ii, Cure model -0.0584 NA NA NA
#> 4 grade_iii, Cure model 0.645 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0119 NA NA NA
#> 2 grade_ii, Survival model 0.290 NA NA NA
#> 3 grade_iii, Survival model 0.133 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.075880 -0.001548 -0.058433 0.644974
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 267.3
#> Residual Deviance: 262.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.075880191 -0.001547522 -0.058433224 0.644974161
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01190674 0.29038822 0.13341740
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0890643817 0.3077174457 0.7306593834 0.9025559044 0.4295658797
#> [6] 0.8349485545 0.1923641728 0.5394448847 0.0142696522 0.1363472548
#> [11] 0.2526546627 0.0142696522 0.1216115225 0.4839976625 0.1673035312
#> [16] 0.0031909394 0.9439122916 0.2526546627 0.0492974549 0.6803074797
#> [21] 0.2886643729 0.0010463555 0.0890643817 0.2526546627 0.2259945106
#> [26] 0.4084173201 0.7955464844 0.1144632382 0.0890643817 0.3470220274
#> [31] 0.0001047706 0.5747247656 0.0600653241 0.1440609358 0.4839976625
#> [36] 0.2886643729 0.9025559044 0.0769890956 0.5747247656 0.7693248593
#> [41] 0.0769890956 0.1673035312 0.7563173084 0.1923641728 0.0600653241
#> [46] 0.4619801531 0.0075578715 0.2793535350 0.9578497439 0.1837982736
#> [51] 0.1440609358 0.4510285511 0.5511220774 0.0492974549 0.0351421024
#> [56] 0.0711140952 0.7053316510 0.7053316510 0.3369169015 0.0106900859
#> [61] 0.5747247656 0.5747247656 0.7434229742 0.2349768847 0.6678018362
#> [66] 0.0257520257 0.7823865371 0.5747247656 0.0031909394 0.3077174457
#> [71] 0.0890643817 0.3772297126 0.3470220274 0.4619801531 0.0351421024
#> [76] 0.2349768847 0.3772297126 0.1216115225 0.8889004122 0.1923641728
#> [81] 0.6803074797 0.8349485545 0.0214336761 0.4839976625 0.0303127088
#> [86] 0.5747247656 0.9718091639 0.4295658797 0.7955464844 0.3470220274
#> [91] 0.3077174457 0.4084173201 0.8752783393 0.3772297126 0.8617102503
#> [96] 0.9299881309 0.1440609358 0.9858588525 0.0351421024 0.7955464844
#> [101] 0.5747247656 0.4839976625 0.1923641728 0.4839976625 0.5628624633
#> [106] 0.5747247656 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 158 45 154 183 79 10 108 29 194 170 134 194.1 105
#> 20.14 17.42 12.63 9.24 16.23 10.53 18.29 15.45 22.40 19.54 17.81 22.40 19.75
#> 6 179 129 70 134.1 90 155 30 164 158.1 134.2 41 192
#> 15.64 18.63 23.41 7.38 17.81 20.94 13.08 17.43 23.60 20.14 17.81 18.02 16.44
#> 107 166 158.2 171 168 57 32 58 6.1 30.1 183.1 150 57.1
#> 11.18 19.98 20.14 16.57 23.72 14.46 20.90 19.34 15.64 17.43 9.24 20.33 14.46
#> 49 150.1 179.1 56 108.1 32.1 26 15 184 25 8 58.1 188
#> 12.19 20.33 18.63 12.21 18.29 20.90 15.77 22.68 17.77 6.32 18.43 19.34 16.16
#> 18 90.1 99 128 140 140.1 106 169 57.2 57.3 177 40 13
#> 15.21 20.94 21.19 20.35 12.68 12.68 16.67 22.41 14.46 14.46 12.53 18.00 14.34
#> 136 43 57.4 129.1 45.1 158.3 130 171.1 26.1 99.1 40.1 130.1 105.1
#> 21.83 12.10 14.46 23.41 17.42 20.14 16.47 16.57 15.77 21.19 18.00 16.47 19.75
#> 187 108.2 155.1 10.1 66 6.2 139 57.5 91 79.1 107.1 171.2 45.2
#> 9.92 18.29 13.08 10.53 22.13 15.64 21.49 14.46 5.33 16.23 11.18 16.57 17.42
#> 192.1 61 130.2 93 16 58.2 127 36 107.2 57.6 6.3 108.3 6.4
#> 16.44 10.12 16.47 10.33 8.71 19.34 3.53 21.19 11.18 14.46 15.64 18.29 15.64
#> 133 57.7 94 53 74 38 176 178 132 67 98 62 103
#> 14.65 14.46 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 185 191 178.1 2 9 80 143 141 162 156 64 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 122 1 144 178.2 191.1 34 147 121 95 20 137 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 27 144.1 120 137.1 64.1 87 12.1 1.1 152 161 178.3 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 38.1 21 65 71 95.1 46 191.2 131 156.1 176.1 84 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 122.1 174 198 147.1 33 148 75 198.1 148.1 98.1 193 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.2 33.1 131.1 31 65.1 62.1 84.1 27.2 163 178.4 80.1 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[67]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01308951 0.63763066 0.60314985
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.445800583 0.006898722 0.243501122
#> grade_iii, Cure model
#> 0.672209426
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 86 23.81 1 58 0 1
#> 97 19.14 1 65 0 1
#> 197 21.60 1 69 1 0
#> 166 19.98 1 48 0 0
#> 192 16.44 1 31 1 0
#> 128 20.35 1 35 0 1
#> 155 13.08 1 26 0 0
#> 197.1 21.60 1 69 1 0
#> 164 23.60 1 76 0 1
#> 169 22.41 1 46 0 0
#> 195 11.76 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 26 15.77 1 49 0 1
#> 36 21.19 1 48 0 1
#> 37 12.52 1 57 1 0
#> 57 14.46 1 45 0 1
#> 76 19.22 1 54 0 1
#> 171 16.57 1 41 0 1
#> 5 16.43 1 51 0 1
#> 157 15.10 1 47 0 0
#> 129 23.41 1 53 1 0
#> 24 23.89 1 38 0 0
#> 123 13.00 1 44 1 0
#> 4 17.64 1 NA 0 1
#> 51 18.23 1 83 0 1
#> 92 22.92 1 47 0 1
#> 57.1 14.46 1 45 0 1
#> 30 17.43 1 78 0 0
#> 181 16.46 1 45 0 1
#> 189 10.51 1 NA 1 0
#> 189.1 10.51 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 93 10.33 1 52 0 1
#> 158 20.14 1 74 1 0
#> 8 18.43 1 32 0 0
#> 77 7.27 1 67 0 1
#> 58 19.34 1 39 0 0
#> 70 7.38 1 30 1 0
#> 5.1 16.43 1 51 0 1
#> 63 22.77 1 31 1 0
#> 175 21.91 1 43 0 0
#> 158.1 20.14 1 74 1 0
#> 158.2 20.14 1 74 1 0
#> 26.1 15.77 1 49 0 1
#> 181.1 16.46 1 45 0 1
#> 15 22.68 1 48 0 0
#> 6 15.64 1 39 0 0
#> 133 14.65 1 57 0 0
#> 85 16.44 1 36 0 0
#> 101 9.97 1 10 0 1
#> 39 15.59 1 37 0 1
#> 68 20.62 1 44 0 0
#> 175.1 21.91 1 43 0 0
#> 133.1 14.65 1 57 0 0
#> 39.1 15.59 1 37 0 1
#> 192.1 16.44 1 31 1 0
#> 136 21.83 1 43 0 1
#> 153.1 21.33 1 55 1 0
#> 91 5.33 1 61 0 1
#> 101.1 9.97 1 10 0 1
#> 149 8.37 1 33 1 0
#> 123.1 13.00 1 44 1 0
#> 97.1 19.14 1 65 0 1
#> 45 17.42 1 54 0 1
#> 130 16.47 1 53 0 1
#> 168.1 23.72 1 70 0 0
#> 6.1 15.64 1 39 0 0
#> 93.1 10.33 1 52 0 1
#> 59 10.16 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 129.1 23.41 1 53 1 0
#> 177 12.53 1 75 0 0
#> 113 22.86 1 34 0 0
#> 129.2 23.41 1 53 1 0
#> 30.1 17.43 1 78 0 0
#> 153.2 21.33 1 55 1 0
#> 184 17.77 1 38 0 0
#> 49 12.19 1 48 1 0
#> 197.2 21.60 1 69 1 0
#> 179 18.63 1 42 0 0
#> 49.1 12.19 1 48 1 0
#> 155.1 13.08 1 26 0 0
#> 99 21.19 1 38 0 1
#> 69 23.23 1 25 0 1
#> 145 10.07 1 65 1 0
#> 145.1 10.07 1 65 1 0
#> 99.1 21.19 1 38 0 1
#> 29 15.45 1 68 1 0
#> 140 12.68 1 59 1 0
#> 125 15.65 1 67 1 0
#> 40 18.00 1 28 1 0
#> 149.1 8.37 1 33 1 0
#> 50 10.02 1 NA 1 0
#> 24.1 23.89 1 38 0 0
#> 25 6.32 1 34 1 0
#> 154 12.63 1 20 1 0
#> 111 17.45 1 47 0 1
#> 181.2 16.46 1 45 0 1
#> 108 18.29 1 39 0 1
#> 153.3 21.33 1 55 1 0
#> 170 19.54 1 43 0 1
#> 114 13.68 1 NA 0 0
#> 139 21.49 1 63 1 0
#> 114.1 13.68 1 NA 0 0
#> 113.1 22.86 1 34 0 0
#> 190 20.81 1 42 1 0
#> 111.1 17.45 1 47 0 1
#> 159 10.55 1 50 0 1
#> 25.1 6.32 1 34 1 0
#> 159.1 10.55 1 50 0 1
#> 107 11.18 1 54 1 0
#> 60 13.15 1 38 1 0
#> 104 24.00 0 50 1 0
#> 1 24.00 0 23 1 0
#> 31 24.00 0 36 0 1
#> 147 24.00 0 76 1 0
#> 2 24.00 0 9 0 0
#> 198 24.00 0 66 0 1
#> 2.1 24.00 0 9 0 0
#> 72 24.00 0 40 0 1
#> 31.1 24.00 0 36 0 1
#> 62 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 137 24.00 0 45 1 0
#> 7 24.00 0 37 1 0
#> 115 24.00 0 NA 1 0
#> 143 24.00 0 51 0 0
#> 72.1 24.00 0 40 0 1
#> 17 24.00 0 38 0 1
#> 94 24.00 0 51 0 1
#> 9 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 178 24.00 0 52 1 0
#> 116 24.00 0 58 0 1
#> 11 24.00 0 42 0 1
#> 33 24.00 0 53 0 0
#> 19 24.00 0 57 0 1
#> 98 24.00 0 34 1 0
#> 147.1 24.00 0 76 1 0
#> 162 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 135 24.00 0 58 1 0
#> 75 24.00 0 21 1 0
#> 118 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 122 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 152 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 132 24.00 0 55 0 0
#> 148 24.00 0 61 1 0
#> 27.1 24.00 0 63 1 0
#> 135.1 24.00 0 58 1 0
#> 182.1 24.00 0 35 0 0
#> 104.1 24.00 0 50 1 0
#> 132.1 24.00 0 55 0 0
#> 19.1 24.00 0 57 0 1
#> 31.2 24.00 0 36 0 1
#> 186 24.00 0 45 1 0
#> 46 24.00 0 71 0 0
#> 196 24.00 0 19 0 0
#> 65.1 24.00 0 57 1 0
#> 115.1 24.00 0 NA 1 0
#> 19.2 24.00 0 57 0 1
#> 119 24.00 0 17 0 0
#> 20.1 24.00 0 46 1 0
#> 71 24.00 0 51 0 0
#> 104.2 24.00 0 50 1 0
#> 141 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 137.1 24.00 0 45 1 0
#> 109 24.00 0 48 0 0
#> 72.2 24.00 0 40 0 1
#> 196.1 24.00 0 19 0 0
#> 44 24.00 0 56 0 0
#> 165 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 191 24.00 0 60 0 1
#> 109.1 24.00 0 48 0 0
#> 2.2 24.00 0 9 0 0
#> 28 24.00 0 67 1 0
#> 67.1 24.00 0 25 0 0
#> 160 24.00 0 31 1 0
#> 143.1 24.00 0 51 0 0
#> 165.1 24.00 0 47 0 0
#> 156 24.00 0 50 1 0
#> 152.1 24.00 0 36 0 1
#> 120 24.00 0 68 0 1
#> 11.1 24.00 0 42 0 1
#> 196.2 24.00 0 19 0 0
#> 163 24.00 0 66 0 0
#> 144 24.00 0 28 0 1
#> 12.1 24.00 0 63 0 0
#> 19.3 24.00 0 57 0 1
#> 27.2 24.00 0 63 1 0
#> 122.1 24.00 0 66 0 0
#> 28.1 24.00 0 67 1 0
#> 3 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 119.1 24.00 0 17 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.446 NA NA NA
#> 2 age, Cure model 0.00690 NA NA NA
#> 3 grade_ii, Cure model 0.244 NA NA NA
#> 4 grade_iii, Cure model 0.672 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0131 NA NA NA
#> 2 grade_ii, Survival model 0.638 NA NA NA
#> 3 grade_iii, Survival model 0.603 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.445801 0.006899 0.243501 0.672209
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 257.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.445800583 0.006898722 0.243501122 0.672209426
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01308951 0.63763066 0.60314985
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.007645353 0.321340047 0.132080592 0.282770207 0.504269658 0.246220888
#> [7] 0.715693911 0.132080592 0.024859021 0.097957569 0.012388689 0.555705226
#> [13] 0.201646507 0.792260167 0.672205115 0.311617020 0.452473079 0.534980330
#> [19] 0.639806622 0.032953370 0.001476472 0.737527233 0.370815411 0.060030920
#> [25] 0.672205115 0.421258671 0.473468234 0.167132861 0.858220197 0.255401757
#> [31] 0.350712869 0.956675811 0.301923802 0.945810084 0.534980330 0.082311674
#> [37] 0.106244879 0.255401757 0.255401757 0.555705226 0.473468234 0.089975924
#> [43] 0.586972034 0.650540880 0.504269658 0.902342721 0.608109369 0.236986329
#> [49] 0.106244879 0.650540880 0.608109369 0.504269658 0.123274905 0.167132861
#> [55] 0.989136695 0.902342721 0.924134748 0.737527233 0.321340047 0.441969091
#> [61] 0.462960344 0.012388689 0.586972034 0.858220197 0.693859486 0.032953370
#> [67] 0.781239428 0.067352363 0.032953370 0.421258671 0.167132861 0.391017861
#> [73] 0.803296689 0.132080592 0.340745910 0.803296689 0.715693911 0.201646507
#> [79] 0.052721258 0.880228368 0.880228368 0.201646507 0.629154479 0.759319552
#> [85] 0.576459246 0.380958332 0.924134748 0.001476472 0.967571183 0.770315058
#> [91] 0.401179851 0.473468234 0.360777723 0.167132861 0.292353441 0.157913387
#> [97] 0.067352363 0.227906698 0.401179851 0.836254063 0.967571183 0.836254063
#> [103] 0.825212533 0.704789425 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 86 97 197 166 192 128 155 197.1 164 169 168 26 36
#> 23.81 19.14 21.60 19.98 16.44 20.35 13.08 21.60 23.60 22.41 23.72 15.77 21.19
#> 37 57 76 171 5 157 129 24 123 51 92 57.1 30
#> 12.52 14.46 19.22 16.57 16.43 15.10 23.41 23.89 13.00 18.23 22.92 14.46 17.43
#> 181 153 93 158 8 77 58 70 5.1 63 175 158.1 158.2
#> 16.46 21.33 10.33 20.14 18.43 7.27 19.34 7.38 16.43 22.77 21.91 20.14 20.14
#> 26.1 181.1 15 6 133 85 101 39 68 175.1 133.1 39.1 192.1
#> 15.77 16.46 22.68 15.64 14.65 16.44 9.97 15.59 20.62 21.91 14.65 15.59 16.44
#> 136 153.1 91 101.1 149 123.1 97.1 45 130 168.1 6.1 93.1 13
#> 21.83 21.33 5.33 9.97 8.37 13.00 19.14 17.42 16.47 23.72 15.64 10.33 14.34
#> 129.1 177 113 129.2 30.1 153.2 184 49 197.2 179 49.1 155.1 99
#> 23.41 12.53 22.86 23.41 17.43 21.33 17.77 12.19 21.60 18.63 12.19 13.08 21.19
#> 69 145 145.1 99.1 29 140 125 40 149.1 24.1 25 154 111
#> 23.23 10.07 10.07 21.19 15.45 12.68 15.65 18.00 8.37 23.89 6.32 12.63 17.45
#> 181.2 108 153.3 170 139 113.1 190 111.1 159 25.1 159.1 107 60
#> 16.46 18.29 21.33 19.54 21.49 22.86 20.81 17.45 10.55 6.32 10.55 11.18 13.15
#> 104 1 31 147 2 198 2.1 72 31.1 62 95 137 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 72.1 17 94 9 27 178 116 11 33 19 98 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 20 135 75 118 65 122 67 152 182 132 148 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 182.1 104.1 132.1 19.1 31.2 186 46 196 65.1 19.2 119 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 104.2 141 146 137.1 109 72.2 196.1 44 165 12 191 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.2 28 67.1 160 143.1 165.1 156 152.1 120 11.1 196.2 163 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.1 19.3 27.2 122.1 28.1 3 176 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[68]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003246326 1.078617353 0.602512938
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.66277927 0.01252987 0.06221898
#> grade_iii, Cure model
#> 0.85679493
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 153 21.33 1 55 1 0
#> 56 12.21 1 60 0 0
#> 37 12.52 1 57 1 0
#> 154 12.63 1 20 1 0
#> 8 18.43 1 32 0 0
#> 79 16.23 1 54 1 0
#> 60 13.15 1 38 1 0
#> 139 21.49 1 63 1 0
#> 50 10.02 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 106 16.67 1 49 1 0
#> 14 12.89 1 21 0 0
#> 61 10.12 1 36 0 1
#> 92 22.92 1 47 0 1
#> 8.1 18.43 1 32 0 0
#> 117 17.46 1 26 0 1
#> 124 9.73 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 16 8.71 1 71 0 1
#> 10 10.53 1 34 0 0
#> 43 12.10 1 61 0 1
#> 85.1 16.44 1 36 0 0
#> 23 16.92 1 61 0 0
#> 52.1 10.42 1 52 0 1
#> 114 13.68 1 NA 0 0
#> 184 17.77 1 38 0 0
#> 107 11.18 1 54 1 0
#> 177 12.53 1 75 0 0
#> 111 17.45 1 47 0 1
#> 181 16.46 1 45 0 1
#> 108 18.29 1 39 0 1
#> 88 18.37 1 47 0 0
#> 52.2 10.42 1 52 0 1
#> 140 12.68 1 59 1 0
#> 106.1 16.67 1 49 1 0
#> 69 23.23 1 25 0 1
#> 25 6.32 1 34 1 0
#> 181.1 16.46 1 45 0 1
#> 37.1 12.52 1 57 1 0
#> 171 16.57 1 41 0 1
#> 89 11.44 1 NA 0 0
#> 86 23.81 1 58 0 1
#> 56.1 12.21 1 60 0 0
#> 78 23.88 1 43 0 0
#> 41 18.02 1 40 1 0
#> 90 20.94 1 50 0 1
#> 187 9.92 1 39 1 0
#> 194 22.40 1 38 0 1
#> 169 22.41 1 46 0 0
#> 89.1 11.44 1 NA 0 0
#> 187.1 9.92 1 39 1 0
#> 129 23.41 1 53 1 0
#> 24 23.89 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 4 17.64 1 NA 0 1
#> 168 23.72 1 70 0 0
#> 140.1 12.68 1 59 1 0
#> 171.1 16.57 1 41 0 1
#> 36 21.19 1 48 0 1
#> 4.1 17.64 1 NA 0 1
#> 183 9.24 1 67 1 0
#> 183.1 9.24 1 67 1 0
#> 128 20.35 1 35 0 1
#> 136 21.83 1 43 0 1
#> 40 18.00 1 28 1 0
#> 184.1 17.77 1 38 0 0
#> 76 19.22 1 54 0 1
#> 52.3 10.42 1 52 0 1
#> 81 14.06 1 34 0 0
#> 164 23.60 1 76 0 1
#> 111.1 17.45 1 47 0 1
#> 29 15.45 1 68 1 0
#> 168.1 23.72 1 70 0 0
#> 49 12.19 1 48 1 0
#> 58 19.34 1 39 0 0
#> 181.2 16.46 1 45 0 1
#> 117.1 17.46 1 26 0 1
#> 128.1 20.35 1 35 0 1
#> 97 19.14 1 65 0 1
#> 57 14.46 1 45 0 1
#> 78.1 23.88 1 43 0 0
#> 184.2 17.77 1 38 0 0
#> 36.1 21.19 1 48 0 1
#> 43.1 12.10 1 61 0 1
#> 78.2 23.88 1 43 0 0
#> 10.1 10.53 1 34 0 0
#> 91 5.33 1 61 0 1
#> 92.1 22.92 1 47 0 1
#> 18 15.21 1 49 1 0
#> 125 15.65 1 67 1 0
#> 79.1 16.23 1 54 1 0
#> 105 19.75 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 168.2 23.72 1 70 0 0
#> 91.1 5.33 1 61 0 1
#> 91.2 5.33 1 61 0 1
#> 123 13.00 1 44 1 0
#> 29.1 15.45 1 68 1 0
#> 25.1 6.32 1 34 1 0
#> 13 14.34 1 54 0 1
#> 14.1 12.89 1 21 0 0
#> 123.1 13.00 1 44 1 0
#> 40.1 18.00 1 28 1 0
#> 18.1 15.21 1 49 1 0
#> 159 10.55 1 50 0 1
#> 190 20.81 1 42 1 0
#> 183.2 9.24 1 67 1 0
#> 40.2 18.00 1 28 1 0
#> 5 16.43 1 51 0 1
#> 184.3 17.77 1 38 0 0
#> 15 22.68 1 48 0 0
#> 28 24.00 0 67 1 0
#> 160 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 163 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 103 24.00 0 56 1 0
#> 47 24.00 0 38 0 1
#> 132 24.00 0 55 0 0
#> 83 24.00 0 6 0 0
#> 176 24.00 0 43 0 1
#> 147 24.00 0 76 1 0
#> 80 24.00 0 41 0 0
#> 87 24.00 0 27 0 0
#> 143 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 147.1 24.00 0 76 1 0
#> 22 24.00 0 52 1 0
#> 3 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 65 24.00 0 57 1 0
#> 65.1 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 67 24.00 0 25 0 0
#> 95 24.00 0 68 0 1
#> 147.2 24.00 0 76 1 0
#> 174 24.00 0 49 1 0
#> 109 24.00 0 48 0 0
#> 178 24.00 0 52 1 0
#> 54 24.00 0 53 1 0
#> 67.1 24.00 0 25 0 0
#> 132.1 24.00 0 55 0 0
#> 152 24.00 0 36 0 1
#> 11.1 24.00 0 42 0 1
#> 109.1 24.00 0 48 0 0
#> 83.1 24.00 0 6 0 0
#> 72 24.00 0 40 0 1
#> 147.3 24.00 0 76 1 0
#> 72.1 24.00 0 40 0 1
#> 3.1 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 98 24.00 0 34 1 0
#> 80.1 24.00 0 41 0 0
#> 103.1 24.00 0 56 1 0
#> 28.1 24.00 0 67 1 0
#> 22.1 24.00 0 52 1 0
#> 95.1 24.00 0 68 0 1
#> 38 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 31 24.00 0 36 0 1
#> 2 24.00 0 9 0 0
#> 72.2 24.00 0 40 0 1
#> 62 24.00 0 71 0 0
#> 2.1 24.00 0 9 0 0
#> 82.1 24.00 0 34 0 0
#> 132.2 24.00 0 55 0 0
#> 122 24.00 0 66 0 0
#> 176.1 24.00 0 43 0 1
#> 73.1 24.00 0 NA 0 1
#> 80.2 24.00 0 41 0 0
#> 163.1 24.00 0 66 0 0
#> 138.1 24.00 0 44 1 0
#> 138.2 24.00 0 44 1 0
#> 82.2 24.00 0 34 0 0
#> 35 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 53 24.00 0 32 0 1
#> 119 24.00 0 17 0 0
#> 17 24.00 0 38 0 1
#> 146 24.00 0 63 1 0
#> 12 24.00 0 63 0 0
#> 146.1 24.00 0 63 1 0
#> 152.1 24.00 0 36 0 1
#> 3.2 24.00 0 31 1 0
#> 143.1 24.00 0 51 0 0
#> 160.2 24.00 0 31 1 0
#> 54.1 24.00 0 53 1 0
#> 64 24.00 0 43 0 0
#> 74 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 119.1 24.00 0 17 0 0
#> 173 24.00 0 19 0 1
#> 103.2 24.00 0 56 1 0
#> 116 24.00 0 58 0 1
#> 28.2 24.00 0 67 1 0
#> 102 24.00 0 49 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.663 NA NA NA
#> 2 age, Cure model 0.0125 NA NA NA
#> 3 grade_ii, Cure model 0.0622 NA NA NA
#> 4 grade_iii, Cure model 0.857 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00325 NA NA NA
#> 2 grade_ii, Survival model 1.08 NA NA NA
#> 3 grade_iii, Survival model 0.603 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.66278 0.01253 0.06222 0.85679
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 253.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.66277927 0.01252987 0.06221898 0.85679493
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003246326 1.078617353 0.602512938
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.43730019 0.88497976 0.87490856 0.86449470 0.55078984 0.76659321
#> [7] 0.82658528 0.42457200 0.74635549 0.69784842 0.84309897 0.94761710
#> [13] 0.33690625 0.55078984 0.65205139 0.92900041 0.97450196 0.91942064
#> [19] 0.89999572 0.74635549 0.69028484 0.92900041 0.62064309 0.90977486
#> [25] 0.86970593 0.66757558 0.72612561 0.57872590 0.56937936 0.92900041
#> [31] 0.85396842 0.69784842 0.32005969 0.97887010 0.72612561 0.87490856
#> [37] 0.71213952 0.19190144 0.88497976 0.11349646 0.58791320 0.47126054
#> [43] 0.95228166 0.39642659 0.38151365 0.95228166 0.30229623 0.04689104
#> [49] 0.04689104 0.21773742 0.85396842 0.71213952 0.44916014 0.96138008
#> [55] 0.96138008 0.49247996 0.41076441 0.59677529 0.62064309 0.53176073
#> [61] 0.92900041 0.82086014 0.28148604 0.66757558 0.78571243 0.21773742
#> [67] 0.89502638 0.52193199 0.72612561 0.65205139 0.49247996 0.54138026
#> [73] 0.80935275 0.11349646 0.62064309 0.44916014 0.89999572 0.11349646
#> [79] 0.91942064 0.98741314 0.33690625 0.79774685 0.77941371 0.76659321
#> [85] 0.51207821 0.68270307 0.21773742 0.98741314 0.98741314 0.83221962
#> [91] 0.78571243 0.97887010 0.81513034 0.84309897 0.83221962 0.59677529
#> [97] 0.79774685 0.91461236 0.48214672 0.96138008 0.59677529 0.75987334
#> [103] 0.62064309 0.36650632 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 153 56 37 154 8 79 60 139 85 106 14 61 92
#> 21.33 12.21 12.52 12.63 18.43 16.23 13.15 21.49 16.44 16.67 12.89 10.12 22.92
#> 8.1 117 52 16 10 43 85.1 23 52.1 184 107 177 111
#> 18.43 17.46 10.42 8.71 10.53 12.10 16.44 16.92 10.42 17.77 11.18 12.53 17.45
#> 181 108 88 52.2 140 106.1 69 25 181.1 37.1 171 86 56.1
#> 16.46 18.29 18.37 10.42 12.68 16.67 23.23 6.32 16.46 12.52 16.57 23.81 12.21
#> 78 41 90 187 194 169 187.1 129 24 24.1 168 140.1 171.1
#> 23.88 18.02 20.94 9.92 22.40 22.41 9.92 23.41 23.89 23.89 23.72 12.68 16.57
#> 36 183 183.1 128 136 40 184.1 76 52.3 81 164 111.1 29
#> 21.19 9.24 9.24 20.35 21.83 18.00 17.77 19.22 10.42 14.06 23.60 17.45 15.45
#> 168.1 49 58 181.2 117.1 128.1 97 57 78.1 184.2 36.1 43.1 78.2
#> 23.72 12.19 19.34 16.46 17.46 20.35 19.14 14.46 23.88 17.77 21.19 12.10 23.88
#> 10.1 91 92.1 18 125 79.1 105 30 168.2 91.1 91.2 123 29.1
#> 10.53 5.33 22.92 15.21 15.65 16.23 19.75 17.43 23.72 5.33 5.33 13.00 15.45
#> 25.1 13 14.1 123.1 40.1 18.1 159 190 183.2 40.2 5 184.3 15
#> 6.32 14.34 12.89 13.00 18.00 15.21 10.55 20.81 9.24 18.00 16.43 17.77 22.68
#> 28 160 156 163 33 103 47 132 83 176 147 80 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 11 147.1 22 3 82 65 65.1 138 67 95 147.2 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 178 54 67.1 132.1 152 11.1 109.1 83.1 72 147.3 72.1 3.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1 33.1 98 80.1 103.1 28.1 22.1 95.1 38 142 31 2 72.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 2.1 82.1 132.2 122 176.1 80.2 163.1 138.1 138.2 82.2 35 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 119 17 146 12 146.1 152.1 3.2 143.1 160.2 54.1 64 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 196 119.1 173 103.2 116 28.2 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[69]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002577723 0.891599369 0.308743932
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.022746175 0.022601919 0.003639012
#> grade_iii, Cure model
#> 0.571687841
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 51 18.23 1 83 0 1
#> 59 10.16 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 79 16.23 1 54 1 0
#> 4 17.64 1 NA 0 1
#> 187 9.92 1 39 1 0
#> 41 18.02 1 40 1 0
#> 60 13.15 1 38 1 0
#> 169 22.41 1 46 0 0
#> 13 14.34 1 54 0 1
#> 133 14.65 1 57 0 0
#> 139 21.49 1 63 1 0
#> 145 10.07 1 65 1 0
#> 26 15.77 1 49 0 1
#> 128 20.35 1 35 0 1
#> 166 19.98 1 48 0 0
#> 77 7.27 1 67 0 1
#> 81 14.06 1 34 0 0
#> 76 19.22 1 54 0 1
#> 170 19.54 1 43 0 1
#> 158 20.14 1 74 1 0
#> 125 15.65 1 67 1 0
#> 134 17.81 1 47 1 0
#> 5 16.43 1 51 0 1
#> 108 18.29 1 39 0 1
#> 86 23.81 1 58 0 1
#> 123 13.00 1 44 1 0
#> 25 6.32 1 34 1 0
#> 78 23.88 1 43 0 0
#> 66 22.13 1 53 0 0
#> 189 10.51 1 NA 1 0
#> 51.1 18.23 1 83 0 1
#> 105 19.75 1 60 0 0
#> 86.1 23.81 1 58 0 1
#> 192 16.44 1 31 1 0
#> 190 20.81 1 42 1 0
#> 150 20.33 1 48 0 0
#> 5.1 16.43 1 51 0 1
#> 170.1 19.54 1 43 0 1
#> 88 18.37 1 47 0 0
#> 166.1 19.98 1 48 0 0
#> 45 17.42 1 54 0 1
#> 179 18.63 1 42 0 0
#> 105.1 19.75 1 60 0 0
#> 133.1 14.65 1 57 0 0
#> 133.2 14.65 1 57 0 0
#> 127 3.53 1 62 0 1
#> 24 23.89 1 38 0 0
#> 81.1 14.06 1 34 0 0
#> 63 22.77 1 31 1 0
#> 199 19.81 1 NA 0 1
#> 164 23.60 1 76 0 1
#> 57 14.46 1 45 0 1
#> 190.1 20.81 1 42 1 0
#> 159 10.55 1 50 0 1
#> 99 21.19 1 38 0 1
#> 140 12.68 1 59 1 0
#> 39 15.59 1 37 0 1
#> 8 18.43 1 32 0 0
#> 154 12.63 1 20 1 0
#> 192.1 16.44 1 31 1 0
#> 169.1 22.41 1 46 0 0
#> 37 12.52 1 57 1 0
#> 167 15.55 1 56 1 0
#> 45.1 17.42 1 54 0 1
#> 105.2 19.75 1 60 0 0
#> 100 16.07 1 60 0 0
#> 184 17.77 1 38 0 0
#> 180.1 14.82 1 37 0 0
#> 69 23.23 1 25 0 1
#> 78.1 23.88 1 43 0 0
#> 4.1 17.64 1 NA 0 1
#> 18 15.21 1 49 1 0
#> 128.1 20.35 1 35 0 1
#> 134.1 17.81 1 47 1 0
#> 149 8.37 1 33 1 0
#> 86.2 23.81 1 58 0 1
#> 90 20.94 1 50 0 1
#> 139.1 21.49 1 63 1 0
#> 42 12.43 1 49 0 1
#> 36 21.19 1 48 0 1
#> 37.1 12.52 1 57 1 0
#> 194 22.40 1 38 0 1
#> 106 16.67 1 49 1 0
#> 24.1 23.89 1 38 0 0
#> 167.1 15.55 1 56 1 0
#> 166.2 19.98 1 48 0 0
#> 30 17.43 1 78 0 0
#> 25.1 6.32 1 34 1 0
#> 145.1 10.07 1 65 1 0
#> 192.2 16.44 1 31 1 0
#> 79.1 16.23 1 54 1 0
#> 136 21.83 1 43 0 1
#> 58 19.34 1 39 0 0
#> 145.2 10.07 1 65 1 0
#> 91 5.33 1 61 0 1
#> 41.1 18.02 1 40 1 0
#> 101 9.97 1 10 0 1
#> 123.1 13.00 1 44 1 0
#> 13.1 14.34 1 54 0 1
#> 113 22.86 1 34 0 0
#> 55 19.34 1 69 0 1
#> 30.1 17.43 1 78 0 0
#> 18.1 15.21 1 49 1 0
#> 155 13.08 1 26 0 0
#> 149.1 8.37 1 33 1 0
#> 124 9.73 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 93 10.33 1 52 0 1
#> 5.2 16.43 1 51 0 1
#> 96 14.54 1 33 0 1
#> 32 20.90 1 37 1 0
#> 196 24.00 0 19 0 0
#> 174 24.00 0 49 1 0
#> 31 24.00 0 36 0 1
#> 161 24.00 0 45 0 0
#> 132 24.00 0 55 0 0
#> 178 24.00 0 52 1 0
#> 9 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 72 24.00 0 40 0 1
#> 62 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 104 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 109 24.00 0 48 0 0
#> 146 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 48 24.00 0 31 1 0
#> 174.1 24.00 0 49 1 0
#> 182 24.00 0 35 0 0
#> 104.1 24.00 0 50 1 0
#> 102 24.00 0 49 0 0
#> 186.1 24.00 0 45 1 0
#> 148 24.00 0 61 1 0
#> 87 24.00 0 27 0 0
#> 53 24.00 0 32 0 1
#> 64 24.00 0 43 0 0
#> 173 24.00 0 19 0 1
#> 156 24.00 0 50 1 0
#> 2 24.00 0 9 0 0
#> 191 24.00 0 60 0 1
#> 9.1 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 67 24.00 0 25 0 0
#> 72.1 24.00 0 40 0 1
#> 174.2 24.00 0 49 1 0
#> 119 24.00 0 17 0 0
#> 65 24.00 0 57 1 0
#> 103 24.00 0 56 1 0
#> 152 24.00 0 36 0 1
#> 38 24.00 0 31 1 0
#> 118.1 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 72.2 24.00 0 40 0 1
#> 165 24.00 0 47 0 0
#> 65.1 24.00 0 57 1 0
#> 27 24.00 0 63 1 0
#> 191.1 24.00 0 60 0 1
#> 64.1 24.00 0 43 0 0
#> 65.2 24.00 0 57 1 0
#> 141 24.00 0 44 1 0
#> 83.1 24.00 0 6 0 0
#> 87.1 24.00 0 27 0 0
#> 193 24.00 0 45 0 1
#> 20 24.00 0 46 1 0
#> 75 24.00 0 21 1 0
#> 193.1 24.00 0 45 0 1
#> 46 24.00 0 71 0 0
#> 116 24.00 0 58 0 1
#> 87.2 24.00 0 27 0 0
#> 17.1 24.00 0 38 0 1
#> 144 24.00 0 28 0 1
#> 112.1 24.00 0 61 0 0
#> 185 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 118.2 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 47 24.00 0 38 0 1
#> 65.3 24.00 0 57 1 0
#> 178.1 24.00 0 52 1 0
#> 21 24.00 0 47 0 0
#> 135 24.00 0 58 1 0
#> 20.1 24.00 0 46 1 0
#> 44 24.00 0 56 0 0
#> 64.2 24.00 0 43 0 0
#> 2.1 24.00 0 9 0 0
#> 103.1 24.00 0 56 1 0
#> 152.1 24.00 0 36 0 1
#> 156.1 24.00 0 50 1 0
#> 162 24.00 0 51 0 0
#> 162.1 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 80 24.00 0 41 0 0
#> 141.1 24.00 0 44 1 0
#> 156.2 24.00 0 50 1 0
#> 165.1 24.00 0 47 0 0
#> 34 24.00 0 36 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.02 NA NA NA
#> 2 age, Cure model 0.0226 NA NA NA
#> 3 grade_ii, Cure model 0.00364 NA NA NA
#> 4 grade_iii, Cure model 0.572 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00258 NA NA NA
#> 2 grade_ii, Survival model 0.892 NA NA NA
#> 3 grade_iii, Survival model 0.309 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.022746 0.022602 0.003639 0.571688
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 267.3
#> Residual Deviance: 259.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.022746175 0.022601919 0.003639012 0.571687841
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002577723 0.891599369 0.308743932
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.59733338 0.80777757 0.73562825 0.95889797 0.61454494 0.87474909
#> [7] 0.25741619 0.85062687 0.82007756 0.33129319 0.93759886 0.75609065
#> [13] 0.42225772 0.46140003 0.97454643 0.86269570 0.55274441 0.51665132
#> [19] 0.45187926 0.76289183 0.63097262 0.71458188 0.58848846 0.13609353
#> [25] 0.88670178 0.97972325 0.08674027 0.30207329 0.59733338 0.48915591
#> [31] 0.13609353 0.69318710 0.40210464 0.44195025 0.71458188 0.51665132
#> [37] 0.57957580 0.46140003 0.67018580 0.56170309 0.48915591 0.82007756
#> [43] 0.82007756 0.99494357 0.03503078 0.86269570 0.24184509 0.18866840
#> [49] 0.84452178 0.40210464 0.92652239 0.35565492 0.89834066 0.76957979
#> [55] 0.57064546 0.90411009 0.69318710 0.25741619 0.90982237 0.77623893
#> [61] 0.67018580 0.48915591 0.74925597 0.64668325 0.80777757 0.20690027
#> [67] 0.08674027 0.79545881 0.42225772 0.63097262 0.96418633 0.13609353
#> [73] 0.37917738 0.33129319 0.92095669 0.35565492 0.90982237 0.28718133
#> [79] 0.68559194 0.03503078 0.77623893 0.46140003 0.65457693 0.97972325
#> [85] 0.93759886 0.69318710 0.73562825 0.31685872 0.53480935 0.93759886
#> [91] 0.98987173 0.61454494 0.95355964 0.88670178 0.85062687 0.22443460
#> [97] 0.53480935 0.65457693 0.79545881 0.88072684 0.96418633 0.78910069
#> [103] 0.93206979 0.71458188 0.83839324 0.39092370 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 51 180 79 187 41 60 169 13 133 139 145 26 128
#> 18.23 14.82 16.23 9.92 18.02 13.15 22.41 14.34 14.65 21.49 10.07 15.77 20.35
#> 166 77 81 76 170 158 125 134 5 108 86 123 25
#> 19.98 7.27 14.06 19.22 19.54 20.14 15.65 17.81 16.43 18.29 23.81 13.00 6.32
#> 78 66 51.1 105 86.1 192 190 150 5.1 170.1 88 166.1 45
#> 23.88 22.13 18.23 19.75 23.81 16.44 20.81 20.33 16.43 19.54 18.37 19.98 17.42
#> 179 105.1 133.1 133.2 127 24 81.1 63 164 57 190.1 159 99
#> 18.63 19.75 14.65 14.65 3.53 23.89 14.06 22.77 23.60 14.46 20.81 10.55 21.19
#> 140 39 8 154 192.1 169.1 37 167 45.1 105.2 100 184 180.1
#> 12.68 15.59 18.43 12.63 16.44 22.41 12.52 15.55 17.42 19.75 16.07 17.77 14.82
#> 69 78.1 18 128.1 134.1 149 86.2 90 139.1 42 36 37.1 194
#> 23.23 23.88 15.21 20.35 17.81 8.37 23.81 20.94 21.49 12.43 21.19 12.52 22.40
#> 106 24.1 167.1 166.2 30 25.1 145.1 192.2 79.1 136 58 145.2 91
#> 16.67 23.89 15.55 19.98 17.43 6.32 10.07 16.44 16.23 21.83 19.34 10.07 5.33
#> 41.1 101 123.1 13.1 113 55 30.1 18.1 155 149.1 29 93 5.2
#> 18.02 9.97 13.00 14.34 22.86 19.34 17.43 15.21 13.08 8.37 15.45 10.33 16.43
#> 96 32 196 174 31 161 132 178 9 118 112 72 62
#> 14.54 20.90 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 104 160 186 109 146 17 48 174.1 182 104.1 102 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 87 53 64 173 156 2 191 9.1 83 67 72.1 174.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 65 103 152 38 118.1 122 72.2 165 65.1 27 191.1 64.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.2 141 83.1 87.1 193 20 75 193.1 46 116 87.2 17.1 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.1 185 71 118.2 74 47 65.3 178.1 21 135 20.1 44 64.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.1 103.1 152.1 156.1 162 162.1 120 80 141.1 156.2 165.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[70]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001665351 0.220596747 -0.104128123
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.088453707 0.001330173 -0.257133552
#> grade_iii, Cure model
#> 0.426246105
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 169 22.41 1 46 0 0
#> 51 18.23 1 83 0 1
#> 60 13.15 1 38 1 0
#> 6 15.64 1 39 0 0
#> 57 14.46 1 45 0 1
#> 110 17.56 1 65 0 1
#> 171 16.57 1 41 0 1
#> 45 17.42 1 54 0 1
#> 78 23.88 1 43 0 0
#> 169.1 22.41 1 46 0 0
#> 69 23.23 1 25 0 1
#> 133 14.65 1 57 0 0
#> 166 19.98 1 48 0 0
#> 45.1 17.42 1 54 0 1
#> 106 16.67 1 49 1 0
#> 105 19.75 1 60 0 0
#> 155 13.08 1 26 0 0
#> 195 11.76 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 32 20.90 1 37 1 0
#> 108 18.29 1 39 0 1
#> 100 16.07 1 60 0 0
#> 15 22.68 1 48 0 0
#> 99 21.19 1 38 0 1
#> 92 22.92 1 47 0 1
#> 128 20.35 1 35 0 1
#> 41 18.02 1 40 1 0
#> 37 12.52 1 57 1 0
#> 63 22.77 1 31 1 0
#> 190 20.81 1 42 1 0
#> 68 20.62 1 44 0 0
#> 166.1 19.98 1 48 0 0
#> 55 19.34 1 69 0 1
#> 96 14.54 1 33 0 1
#> 51.1 18.23 1 83 0 1
#> 183 9.24 1 67 1 0
#> 187 9.92 1 39 1 0
#> 5 16.43 1 51 0 1
#> 58 19.34 1 39 0 0
#> 88.1 18.37 1 47 0 0
#> 55.1 19.34 1 69 0 1
#> 52 10.42 1 52 0 1
#> 101 9.97 1 10 0 1
#> 130 16.47 1 53 0 1
#> 30 17.43 1 78 0 0
#> 58.1 19.34 1 39 0 0
#> 101.1 9.97 1 10 0 1
#> 56 12.21 1 60 0 0
#> 190.1 20.81 1 42 1 0
#> 158 20.14 1 74 1 0
#> 41.1 18.02 1 40 1 0
#> 117 17.46 1 26 0 1
#> 101.2 9.97 1 10 0 1
#> 194 22.40 1 38 0 1
#> 169.2 22.41 1 46 0 0
#> 92.1 22.92 1 47 0 1
#> 175 21.91 1 43 0 0
#> 8 18.43 1 32 0 0
#> 183.1 9.24 1 67 1 0
#> 134 17.81 1 47 1 0
#> 66 22.13 1 53 0 0
#> 14 12.89 1 21 0 0
#> 59 10.16 1 NA 1 0
#> 6.1 15.64 1 39 0 0
#> 55.2 19.34 1 69 0 1
#> 51.2 18.23 1 83 0 1
#> 63.1 22.77 1 31 1 0
#> 134.1 17.81 1 47 1 0
#> 23 16.92 1 61 0 0
#> 134.2 17.81 1 47 1 0
#> 93 10.33 1 52 0 1
#> 199 19.81 1 NA 0 1
#> 26 15.77 1 49 0 1
#> 164 23.60 1 76 0 1
#> 59.1 10.16 1 NA 1 0
#> 88.2 18.37 1 47 0 0
#> 40 18.00 1 28 1 0
#> 195.1 11.76 1 NA 1 0
#> 106.1 16.67 1 49 1 0
#> 157 15.10 1 47 0 0
#> 69.1 23.23 1 25 0 1
#> 90 20.94 1 50 0 1
#> 99.1 21.19 1 38 0 1
#> 56.1 12.21 1 60 0 0
#> 179 18.63 1 42 0 0
#> 61 10.12 1 36 0 1
#> 179.1 18.63 1 42 0 0
#> 36 21.19 1 48 0 1
#> 127 3.53 1 62 0 1
#> 136 21.83 1 43 0 1
#> 180 14.82 1 37 0 0
#> 158.1 20.14 1 74 1 0
#> 105.1 19.75 1 60 0 0
#> 99.2 21.19 1 38 0 1
#> 97 19.14 1 65 0 1
#> 139 21.49 1 63 1 0
#> 167 15.55 1 56 1 0
#> 164.1 23.60 1 76 0 1
#> 136.1 21.83 1 43 0 1
#> 113 22.86 1 34 0 0
#> 190.2 20.81 1 42 1 0
#> 43 12.10 1 61 0 1
#> 4 17.64 1 NA 0 1
#> 81 14.06 1 34 0 0
#> 18 15.21 1 49 1 0
#> 100.1 16.07 1 60 0 0
#> 59.2 10.16 1 NA 1 0
#> 63.2 22.77 1 31 1 0
#> 25 6.32 1 34 1 0
#> 195.2 11.76 1 NA 1 0
#> 8.1 18.43 1 32 0 0
#> 70 7.38 1 30 1 0
#> 143 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 102 24.00 0 49 0 0
#> 2 24.00 0 9 0 0
#> 9 24.00 0 31 1 0
#> 102.1 24.00 0 49 0 0
#> 142 24.00 0 53 0 0
#> 27 24.00 0 63 1 0
#> 165 24.00 0 47 0 0
#> 1 24.00 0 23 1 0
#> 143.1 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 64 24.00 0 43 0 0
#> 3 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 135 24.00 0 58 1 0
#> 138 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 38 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 104 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 84.1 24.00 0 39 0 1
#> 191 24.00 0 60 0 1
#> 11 24.00 0 42 0 1
#> 148 24.00 0 61 1 0
#> 73 24.00 0 NA 0 1
#> 165.1 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 193 24.00 0 45 0 1
#> 131 24.00 0 66 0 0
#> 73.1 24.00 0 NA 0 1
#> 21 24.00 0 47 0 0
#> 162 24.00 0 51 0 0
#> 84.2 24.00 0 39 0 1
#> 200 24.00 0 64 0 0
#> 163 24.00 0 66 0 0
#> 142.1 24.00 0 53 0 0
#> 172 24.00 0 41 0 0
#> 20 24.00 0 46 1 0
#> 21.1 24.00 0 47 0 0
#> 104.1 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 28 24.00 0 67 1 0
#> 172.1 24.00 0 41 0 0
#> 20.1 24.00 0 46 1 0
#> 121.1 24.00 0 57 1 0
#> 65 24.00 0 57 1 0
#> 144.1 24.00 0 28 0 1
#> 72 24.00 0 40 0 1
#> 160 24.00 0 31 1 0
#> 191.1 24.00 0 60 0 1
#> 156 24.00 0 50 1 0
#> 142.2 24.00 0 53 0 0
#> 121.2 24.00 0 57 1 0
#> 54 24.00 0 53 1 0
#> 115.1 24.00 0 NA 1 0
#> 19 24.00 0 57 0 1
#> 82 24.00 0 34 0 0
#> 173 24.00 0 19 0 1
#> 103 24.00 0 56 1 0
#> 193.1 24.00 0 45 0 1
#> 178 24.00 0 52 1 0
#> 67 24.00 0 25 0 0
#> 9.1 24.00 0 31 1 0
#> 191.2 24.00 0 60 0 1
#> 95 24.00 0 68 0 1
#> 80 24.00 0 41 0 0
#> 112.1 24.00 0 61 0 0
#> 104.2 24.00 0 50 1 0
#> 83 24.00 0 6 0 0
#> 71 24.00 0 51 0 0
#> 53 24.00 0 32 0 1
#> 94 24.00 0 51 0 1
#> 22 24.00 0 52 1 0
#> 27.1 24.00 0 63 1 0
#> 172.2 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 135.1 24.00 0 58 1 0
#> 44 24.00 0 56 0 0
#> 64.1 24.00 0 43 0 0
#> 152.1 24.00 0 36 0 1
#> 31 24.00 0 36 0 1
#> 54.1 24.00 0 53 1 0
#> 109 24.00 0 48 0 0
#> 119 24.00 0 17 0 0
#> 120.1 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0885 NA NA NA
#> 2 age, Cure model 0.00133 NA NA NA
#> 3 grade_ii, Cure model -0.257 NA NA NA
#> 4 grade_iii, Cure model 0.426 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00167 NA NA NA
#> 2 grade_ii, Survival model 0.221 NA NA NA
#> 3 grade_iii, Survival model -0.104 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.08845 0.00133 -0.25713 0.42625
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.5
#> Residual Deviance: 254.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.088453707 0.001330173 -0.257133552 0.426246105
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001665351 0.220596747 -0.104128123
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.149094026 0.538065954 0.834414632 0.745858834 0.816737527 0.620156075
#> [7] 0.692222733 0.647364535 0.009892147 0.149094026 0.047643135 0.799065054
#> [13] 0.370476061 0.647364535 0.674413940 0.389517205 0.843219822 0.500987128
#> [19] 0.292321657 0.528667020 0.719128018 0.138077700 0.242501542 0.071083980
#> [25] 0.341433766 0.565724010 0.860818837 0.107409728 0.302622671 0.331527084
#> [31] 0.370476061 0.408461238 0.807898971 0.538065954 0.956794115 0.948050163
#> [37] 0.710157550 0.408461238 0.500987128 0.408461238 0.895733296 0.921980778
#> [43] 0.701189238 0.638304387 0.408461238 0.921980778 0.869583497 0.302622671
#> [49] 0.351353363 0.565724010 0.629226369 0.921980778 0.179290385 0.149094026
#> [55] 0.071083980 0.200666960 0.482274936 0.956794115 0.593339647 0.190006326
#> [61] 0.852020946 0.745858834 0.408461238 0.538065954 0.107409728 0.593339647
#> [67] 0.665365115 0.593339647 0.904480268 0.736910750 0.025094156 0.500987128
#> [73] 0.584115296 0.674413940 0.781371457 0.047643135 0.281900960 0.242501542
#> [79] 0.869583497 0.463523016 0.913228711 0.463523016 0.242501542 0.991367460
#> [85] 0.211285857 0.790221402 0.351353363 0.389517205 0.242501542 0.454022181
#> [91] 0.232056669 0.763619249 0.025094156 0.211285857 0.094797134 0.302622671
#> [97] 0.886987809 0.825578835 0.772513344 0.719128018 0.107409728 0.982734986
#> [103] 0.482274936 0.974078221 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 169 51 60 6 57 110 171 45 78 169.1 69 133 166
#> 22.41 18.23 13.15 15.64 14.46 17.56 16.57 17.42 23.88 22.41 23.23 14.65 19.98
#> 45.1 106 105 155 88 32 108 100 15 99 92 128 41
#> 17.42 16.67 19.75 13.08 18.37 20.90 18.29 16.07 22.68 21.19 22.92 20.35 18.02
#> 37 63 190 68 166.1 55 96 51.1 183 187 5 58 88.1
#> 12.52 22.77 20.81 20.62 19.98 19.34 14.54 18.23 9.24 9.92 16.43 19.34 18.37
#> 55.1 52 101 130 30 58.1 101.1 56 190.1 158 41.1 117 101.2
#> 19.34 10.42 9.97 16.47 17.43 19.34 9.97 12.21 20.81 20.14 18.02 17.46 9.97
#> 194 169.2 92.1 175 8 183.1 134 66 14 6.1 55.2 51.2 63.1
#> 22.40 22.41 22.92 21.91 18.43 9.24 17.81 22.13 12.89 15.64 19.34 18.23 22.77
#> 134.1 23 134.2 93 26 164 88.2 40 106.1 157 69.1 90 99.1
#> 17.81 16.92 17.81 10.33 15.77 23.60 18.37 18.00 16.67 15.10 23.23 20.94 21.19
#> 56.1 179 61 179.1 36 127 136 180 158.1 105.1 99.2 97 139
#> 12.21 18.63 10.12 18.63 21.19 3.53 21.83 14.82 20.14 19.75 21.19 19.14 21.49
#> 167 164.1 136.1 113 190.2 43 81 18 100.1 63.2 25 8.1 70
#> 15.55 23.60 21.83 22.86 20.81 12.10 14.06 15.21 16.07 22.77 6.32 18.43 7.38
#> 143 152 75 102 2 9 102.1 142 27 165 1 143.1 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 3 84 135 138 112 38 120 104 146 84.1 191 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 165.1 193 131 21 162 84.2 200 163 142.1 172 20 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 121 28 172.1 20.1 121.1 65 144.1 72 160 191.1 156 142.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.2 54 19 82 173 103 193.1 178 67 9.1 191.2 95 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.1 104.2 83 71 53 94 22 27.1 172.2 198 135.1 44 64.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 31 54.1 109 119 120.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[71]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01712362 0.45174659 0.31532580
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.135359943 -0.002140757 0.078554505
#> grade_iii, Cure model
#> 0.315501584
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 187 9.92 1 39 1 0
#> 184 17.77 1 38 0 0
#> 154 12.63 1 20 1 0
#> 39 15.59 1 37 0 1
#> 129 23.41 1 53 1 0
#> 29 15.45 1 68 1 0
#> 23 16.92 1 61 0 0
#> 199 19.81 1 NA 0 1
#> 190 20.81 1 42 1 0
#> 91 5.33 1 61 0 1
#> 154.1 12.63 1 20 1 0
#> 149 8.37 1 33 1 0
#> 100 16.07 1 60 0 0
#> 4 17.64 1 NA 0 1
#> 92 22.92 1 47 0 1
#> 171 16.57 1 41 0 1
#> 153 21.33 1 55 1 0
#> 155 13.08 1 26 0 0
#> 134 17.81 1 47 1 0
#> 42 12.43 1 49 0 1
#> 91.1 5.33 1 61 0 1
#> 127 3.53 1 62 0 1
#> 50 10.02 1 NA 1 0
#> 42.1 12.43 1 49 0 1
#> 153.1 21.33 1 55 1 0
#> 41 18.02 1 40 1 0
#> 106 16.67 1 49 1 0
#> 180 14.82 1 37 0 0
#> 68 20.62 1 44 0 0
#> 49 12.19 1 48 1 0
#> 111 17.45 1 47 0 1
#> 66 22.13 1 53 0 0
#> 117 17.46 1 26 0 1
#> 157 15.10 1 47 0 0
#> 89 11.44 1 NA 0 0
#> 110 17.56 1 65 0 1
#> 168 23.72 1 70 0 0
#> 117.1 17.46 1 26 0 1
#> 164 23.60 1 76 0 1
#> 45 17.42 1 54 0 1
#> 192 16.44 1 31 1 0
#> 168.1 23.72 1 70 0 0
#> 129.1 23.41 1 53 1 0
#> 68.1 20.62 1 44 0 0
#> 134.1 17.81 1 47 1 0
#> 4.1 17.64 1 NA 0 1
#> 86 23.81 1 58 0 1
#> 149.1 8.37 1 33 1 0
#> 50.1 10.02 1 NA 1 0
#> 100.1 16.07 1 60 0 0
#> 133 14.65 1 57 0 0
#> 51 18.23 1 83 0 1
#> 195 11.76 1 NA 1 0
#> 49.1 12.19 1 48 1 0
#> 100.2 16.07 1 60 0 0
#> 49.2 12.19 1 48 1 0
#> 108 18.29 1 39 0 1
#> 8 18.43 1 32 0 0
#> 124 9.73 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 139 21.49 1 63 1 0
#> 14 12.89 1 21 0 0
#> 145 10.07 1 65 1 0
#> 195.1 11.76 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 99 21.19 1 38 0 1
#> 124.1 9.73 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 32 20.90 1 37 1 0
#> 105 19.75 1 60 0 0
#> 16 8.71 1 71 0 1
#> 125 15.65 1 67 1 0
#> 197 21.60 1 69 1 0
#> 15 22.68 1 48 0 0
#> 140 12.68 1 59 1 0
#> 136.1 21.83 1 43 0 1
#> 110.1 17.56 1 65 0 1
#> 113 22.86 1 34 0 0
#> 6 15.64 1 39 0 0
#> 192.1 16.44 1 31 1 0
#> 99.1 21.19 1 38 0 1
#> 61 10.12 1 36 0 1
#> 187.1 9.92 1 39 1 0
#> 154.2 12.63 1 20 1 0
#> 155.1 13.08 1 26 0 0
#> 91.2 5.33 1 61 0 1
#> 89.1 11.44 1 NA 0 0
#> 100.3 16.07 1 60 0 0
#> 99.2 21.19 1 38 0 1
#> 195.2 11.76 1 NA 1 0
#> 105.1 19.75 1 60 0 0
#> 29.1 15.45 1 68 1 0
#> 197.1 21.60 1 69 1 0
#> 18 15.21 1 49 1 0
#> 5 16.43 1 51 0 1
#> 25 6.32 1 34 1 0
#> 129.2 23.41 1 53 1 0
#> 58.1 19.34 1 39 0 0
#> 180.1 14.82 1 37 0 0
#> 25.1 6.32 1 34 1 0
#> 24 23.89 1 38 0 0
#> 157.1 15.10 1 47 0 0
#> 43 12.10 1 61 0 1
#> 110.2 17.56 1 65 0 1
#> 125.1 15.65 1 67 1 0
#> 32.1 20.90 1 37 1 0
#> 40 18.00 1 28 1 0
#> 77 7.27 1 67 0 1
#> 149.2 8.37 1 33 1 0
#> 168.2 23.72 1 70 0 0
#> 59 10.16 1 NA 1 0
#> 180.2 14.82 1 37 0 0
#> 118 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 147 24.00 0 76 1 0
#> 27 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 17 24.00 0 38 0 1
#> 193 24.00 0 45 0 1
#> 38 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 33 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 109 24.00 0 48 0 0
#> 62 24.00 0 71 0 0
#> 82.1 24.00 0 34 0 0
#> 115 24.00 0 NA 1 0
#> 141 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 72 24.00 0 40 0 1
#> 116 24.00 0 58 0 1
#> 115.1 24.00 0 NA 1 0
#> 74 24.00 0 43 0 1
#> 160 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 176 24.00 0 43 0 1
#> 116.1 24.00 0 58 0 1
#> 17.1 24.00 0 38 0 1
#> 131 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 163 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 142.1 24.00 0 53 0 0
#> 156 24.00 0 50 1 0
#> 94 24.00 0 51 0 1
#> 152 24.00 0 36 0 1
#> 156.1 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 28 24.00 0 67 1 0
#> 122 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 17.2 24.00 0 38 0 1
#> 148 24.00 0 61 1 0
#> 19 24.00 0 57 0 1
#> 22 24.00 0 52 1 0
#> 118.1 24.00 0 44 1 0
#> 146.1 24.00 0 63 1 0
#> 186 24.00 0 45 1 0
#> 104 24.00 0 50 1 0
#> 174 24.00 0 49 1 0
#> 65 24.00 0 57 1 0
#> 34 24.00 0 36 0 0
#> 34.1 24.00 0 36 0 0
#> 156.2 24.00 0 50 1 0
#> 7.1 24.00 0 37 1 0
#> 94.1 24.00 0 51 0 1
#> 182 24.00 0 35 0 0
#> 20 24.00 0 46 1 0
#> 200 24.00 0 64 0 0
#> 142.2 24.00 0 53 0 0
#> 115.2 24.00 0 NA 1 0
#> 65.1 24.00 0 57 1 0
#> 98 24.00 0 34 1 0
#> 118.2 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 121 24.00 0 57 1 0
#> 132 24.00 0 55 0 0
#> 20.1 24.00 0 46 1 0
#> 31 24.00 0 36 0 1
#> 72.1 24.00 0 40 0 1
#> 165.1 24.00 0 47 0 0
#> 172 24.00 0 41 0 0
#> 94.2 24.00 0 51 0 1
#> 156.3 24.00 0 50 1 0
#> 186.1 24.00 0 45 1 0
#> 198 24.00 0 66 0 1
#> 44 24.00 0 56 0 0
#> 191 24.00 0 60 0 1
#> 121.1 24.00 0 57 1 0
#> 118.3 24.00 0 44 1 0
#> 163.1 24.00 0 66 0 0
#> 146.2 24.00 0 63 1 0
#> 2 24.00 0 9 0 0
#> 182.1 24.00 0 35 0 0
#> 176.1 24.00 0 43 0 1
#> 148.1 24.00 0 61 1 0
#> 95 24.00 0 68 0 1
#> 131.1 24.00 0 66 0 0
#> 98.1 24.00 0 34 1 0
#> 80 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.135 NA NA NA
#> 2 age, Cure model -0.00214 NA NA NA
#> 3 grade_ii, Cure model 0.0786 NA NA NA
#> 4 grade_iii, Cure model 0.316 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0171 NA NA NA
#> 2 grade_ii, Survival model 0.452 NA NA NA
#> 3 grade_iii, Survival model 0.315 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.135360 -0.002141 0.078555 0.315502
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 254
#> Residual Deviance: 253.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.135359943 -0.002140757 0.078554505 0.315501584
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01712362 0.45174659 0.31532580
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 7.934241e-01 2.134853e-01 6.309189e-01 4.400325e-01 6.745993e-03
#> [6] 4.526623e-01 2.922243e-01 9.347073e-02 9.346706e-01 6.309189e-01
#> [11] 8.400829e-01 3.572585e-01 1.375909e-02 3.136815e-01 5.239232e-02
#> [16] 5.731161e-01 1.955209e-01 6.736683e-01 9.346706e-01 9.833509e-01
#> [21] 6.736683e-01 5.239232e-02 1.776376e-01 3.028919e-01 5.180245e-01
#> [26] 9.998728e-02 7.029895e-01 2.715552e-01 2.420959e-02 2.517299e-01
#> [31] 4.913918e-01 2.228576e-01 9.272740e-04 2.517299e-01 4.373349e-03
#> [36] 2.818033e-01 3.245916e-01 9.272740e-04 6.745993e-03 9.998728e-02
#> [41] 1.955209e-01 3.510055e-04 8.400829e-01 3.572585e-01 5.589172e-01
#> [46] 1.687944e-01 7.029895e-01 3.572585e-01 7.029895e-01 1.602508e-01
#> [51] 1.518404e-01 1.281289e-01 4.690273e-02 6.016642e-01 7.779444e-01
#> [56] 1.436221e-01 6.366871e-02 2.842939e-02 8.108747e-02 1.134986e-01
#> [61] 8.243136e-01 4.031475e-01 3.706961e-02 2.038775e-02 6.162172e-01
#> [66] 2.842939e-02 2.228576e-01 1.692993e-02 4.275009e-01 3.245916e-01
#> [71] 6.366871e-02 7.626123e-01 7.934241e-01 6.309189e-01 5.731161e-01
#> [76] 9.346706e-01 3.572585e-01 6.366871e-02 1.134986e-01 4.526623e-01
#> [81] 3.706961e-02 4.782882e-01 3.461538e-01 9.027960e-01 6.745993e-03
#> [86] 1.281289e-01 5.180245e-01 9.027960e-01 5.162078e-05 4.913918e-01
#> [91] 7.473600e-01 2.228576e-01 4.031475e-01 8.108747e-02 1.865734e-01
#> [96] 8.867853e-01 8.400829e-01 9.272740e-04 5.180245e-01 0.000000e+00
#> [101] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 187 184 154 39 129 29 23 190 91 154.1 149 100 92
#> 9.92 17.77 12.63 15.59 23.41 15.45 16.92 20.81 5.33 12.63 8.37 16.07 22.92
#> 171 153 155 134 42 91.1 127 42.1 153.1 41 106 180 68
#> 16.57 21.33 13.08 17.81 12.43 5.33 3.53 12.43 21.33 18.02 16.67 14.82 20.62
#> 49 111 66 117 157 110 168 117.1 164 45 192 168.1 129.1
#> 12.19 17.45 22.13 17.46 15.10 17.56 23.72 17.46 23.60 17.42 16.44 23.72 23.41
#> 68.1 134.1 86 149.1 100.1 133 51 49.1 100.2 49.2 108 8 58
#> 20.62 17.81 23.81 8.37 16.07 14.65 18.23 12.19 16.07 12.19 18.29 18.43 19.34
#> 139 14 145 97 99 136 32 105 16 125 197 15 140
#> 21.49 12.89 10.07 19.14 21.19 21.83 20.90 19.75 8.71 15.65 21.60 22.68 12.68
#> 136.1 110.1 113 6 192.1 99.1 61 187.1 154.2 155.1 91.2 100.3 99.2
#> 21.83 17.56 22.86 15.64 16.44 21.19 10.12 9.92 12.63 13.08 5.33 16.07 21.19
#> 105.1 29.1 197.1 18 5 25 129.2 58.1 180.1 25.1 24 157.1 43
#> 19.75 15.45 21.60 15.21 16.43 6.32 23.41 19.34 14.82 6.32 23.89 15.10 12.10
#> 110.2 125.1 32.1 40 77 149.2 168.2 180.2 118 173 147 27 64
#> 17.56 15.65 20.90 18.00 7.27 8.37 23.72 14.82 24.00 24.00 24.00 24.00 24.00
#> 17 193 38 142 33 82 109 62 82.1 141 146 72 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 160 196 176 116.1 17.1 131 120 163 165 142.1 156 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 156.1 7 28 122 21 17.2 148 19 22 118.1 146.1 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 174 65 34 34.1 156.2 7.1 94.1 182 20 200 142.2 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 118.2 151 121 132 20.1 31 72.1 165.1 172 94.2 156.3 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 44 191 121.1 118.3 163.1 146.2 2 182.1 176.1 148.1 95 131.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 80
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[72]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002591651 0.715391074 0.224845965
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.26820212 0.02394532 0.52479787
#> grade_iii, Cure model
#> 0.88975880
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 81 14.06 1 34 0 0
#> 56 12.21 1 60 0 0
#> 40 18.00 1 28 1 0
#> 133 14.65 1 57 0 0
#> 171 16.57 1 41 0 1
#> 86 23.81 1 58 0 1
#> 184 17.77 1 38 0 0
#> 32 20.90 1 37 1 0
#> 153 21.33 1 55 1 0
#> 16 8.71 1 71 0 1
#> 101 9.97 1 10 0 1
#> 69 23.23 1 25 0 1
#> 170 19.54 1 43 0 1
#> 41 18.02 1 40 1 0
#> 145 10.07 1 65 1 0
#> 89 11.44 1 NA 0 0
#> 100 16.07 1 60 0 0
#> 70 7.38 1 30 1 0
#> 37 12.52 1 57 1 0
#> 187 9.92 1 39 1 0
#> 183 9.24 1 67 1 0
#> 168 23.72 1 70 0 0
#> 159 10.55 1 50 0 1
#> 100.1 16.07 1 60 0 0
#> 139 21.49 1 63 1 0
#> 25 6.32 1 34 1 0
#> 97 19.14 1 65 0 1
#> 168.1 23.72 1 70 0 0
#> 169 22.41 1 46 0 0
#> 6 15.64 1 39 0 0
#> 96 14.54 1 33 0 1
#> 139.1 21.49 1 63 1 0
#> 105 19.75 1 60 0 0
#> 106 16.67 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 195 11.76 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 32.1 20.90 1 37 1 0
#> 197 21.60 1 69 1 0
#> 30 17.43 1 78 0 0
#> 113 22.86 1 34 0 0
#> 168.2 23.72 1 70 0 0
#> 187.1 9.92 1 39 1 0
#> 78 23.88 1 43 0 0
#> 154 12.63 1 20 1 0
#> 107 11.18 1 54 1 0
#> 92 22.92 1 47 0 1
#> 180 14.82 1 37 0 0
#> 190 20.81 1 42 1 0
#> 85 16.44 1 36 0 0
#> 153.1 21.33 1 55 1 0
#> 133.1 14.65 1 57 0 0
#> 149 8.37 1 33 1 0
#> 78.1 23.88 1 43 0 0
#> 106.1 16.67 1 49 1 0
#> 179 18.63 1 42 0 0
#> 150 20.33 1 48 0 0
#> 125 15.65 1 67 1 0
#> 134 17.81 1 47 1 0
#> 58 19.34 1 39 0 0
#> 187.2 9.92 1 39 1 0
#> 29 15.45 1 68 1 0
#> 99 21.19 1 38 0 1
#> 181 16.46 1 45 0 1
#> 60 13.15 1 38 1 0
#> 59 10.16 1 NA 1 0
#> 154.1 12.63 1 20 1 0
#> 192 16.44 1 31 1 0
#> 194 22.40 1 38 0 1
#> 130 16.47 1 53 0 1
#> 89.1 11.44 1 NA 0 0
#> 43 12.10 1 61 0 1
#> 79 16.23 1 54 1 0
#> 125.1 15.65 1 67 1 0
#> 100.2 16.07 1 60 0 0
#> 29.1 15.45 1 68 1 0
#> 134.1 17.81 1 47 1 0
#> 158 20.14 1 74 1 0
#> 43.1 12.10 1 61 0 1
#> 69.1 23.23 1 25 0 1
#> 123 13.00 1 44 1 0
#> 183.1 9.24 1 67 1 0
#> 52 10.42 1 52 0 1
#> 37.1 12.52 1 57 1 0
#> 30.1 17.43 1 78 0 0
#> 99.1 21.19 1 38 0 1
#> 57 14.46 1 45 0 1
#> 184.1 17.77 1 38 0 0
#> 91 5.33 1 61 0 1
#> 153.2 21.33 1 55 1 0
#> 16.1 8.71 1 71 0 1
#> 10 10.53 1 34 0 0
#> 167 15.55 1 56 1 0
#> 51 18.23 1 83 0 1
#> 70.1 7.38 1 30 1 0
#> 40.1 18.00 1 28 1 0
#> 188 16.16 1 46 0 1
#> 128 20.35 1 35 0 1
#> 184.2 17.77 1 38 0 0
#> 14 12.89 1 21 0 0
#> 29.2 15.45 1 68 1 0
#> 30.2 17.43 1 78 0 0
#> 133.2 14.65 1 57 0 0
#> 113.1 22.86 1 34 0 0
#> 92.1 22.92 1 47 0 1
#> 14.1 12.89 1 21 0 0
#> 13 14.34 1 54 0 1
#> 194.1 22.40 1 38 0 1
#> 199 19.81 1 NA 0 1
#> 168.3 23.72 1 70 0 0
#> 124 9.73 1 NA 1 0
#> 173 24.00 0 19 0 1
#> 83 24.00 0 6 0 0
#> 82 24.00 0 34 0 0
#> 34 24.00 0 36 0 0
#> 120 24.00 0 68 0 1
#> 22 24.00 0 52 1 0
#> 143 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 75 24.00 0 21 1 0
#> 141 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 62 24.00 0 71 0 0
#> 27 24.00 0 63 1 0
#> 191.1 24.00 0 60 0 1
#> 147 24.00 0 76 1 0
#> 122 24.00 0 66 0 0
#> 141.1 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 1 24.00 0 23 1 0
#> 1.1 24.00 0 23 1 0
#> 151 24.00 0 42 0 0
#> 67 24.00 0 25 0 0
#> 135 24.00 0 58 1 0
#> 138 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 126 24.00 0 48 0 0
#> 191.2 24.00 0 60 0 1
#> 172 24.00 0 41 0 0
#> 146 24.00 0 63 1 0
#> 112 24.00 0 61 0 0
#> 12 24.00 0 63 0 0
#> 115 24.00 0 NA 1 0
#> 146.1 24.00 0 63 1 0
#> 72 24.00 0 40 0 1
#> 67.1 24.00 0 25 0 0
#> 2 24.00 0 9 0 0
#> 165.1 24.00 0 47 0 0
#> 104 24.00 0 50 1 0
#> 122.1 24.00 0 66 0 0
#> 173.1 24.00 0 19 0 1
#> 142 24.00 0 53 0 0
#> 87 24.00 0 27 0 0
#> 121 24.00 0 57 1 0
#> 74 24.00 0 43 0 1
#> 141.2 24.00 0 44 1 0
#> 182.1 24.00 0 35 0 0
#> 72.1 24.00 0 40 0 1
#> 7 24.00 0 37 1 0
#> 75.1 24.00 0 21 1 0
#> 109 24.00 0 48 0 0
#> 64 24.00 0 43 0 0
#> 160 24.00 0 31 1 0
#> 73.1 24.00 0 NA 0 1
#> 116 24.00 0 58 0 1
#> 65 24.00 0 57 1 0
#> 126.1 24.00 0 48 0 0
#> 87.1 24.00 0 27 0 0
#> 87.2 24.00 0 27 0 0
#> 132 24.00 0 55 0 0
#> 151.1 24.00 0 42 0 0
#> 178 24.00 0 52 1 0
#> 11 24.00 0 42 0 1
#> 83.1 24.00 0 6 0 0
#> 143.1 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 73.2 24.00 0 NA 0 1
#> 126.2 24.00 0 48 0 0
#> 48.1 24.00 0 31 1 0
#> 120.1 24.00 0 68 0 1
#> 65.1 24.00 0 57 1 0
#> 12.1 24.00 0 63 0 0
#> 172.1 24.00 0 41 0 0
#> 17 24.00 0 38 0 1
#> 142.1 24.00 0 53 0 0
#> 31 24.00 0 36 0 1
#> 196 24.00 0 19 0 0
#> 196.1 24.00 0 19 0 0
#> 34.1 24.00 0 36 0 0
#> 67.2 24.00 0 25 0 0
#> 196.2 24.00 0 19 0 0
#> 1.2 24.00 0 23 1 0
#> 75.2 24.00 0 21 1 0
#> 20.1 24.00 0 46 1 0
#> 104.1 24.00 0 50 1 0
#> 21 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.27 NA NA NA
#> 2 age, Cure model 0.0239 NA NA NA
#> 3 grade_ii, Cure model 0.525 NA NA NA
#> 4 grade_iii, Cure model 0.890 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00259 NA NA NA
#> 2 grade_ii, Survival model 0.715 NA NA NA
#> 3 grade_iii, Survival model 0.225 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.26820 0.02395 0.52480 0.88976
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 259.7
#> Residual Deviance: 247.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.26820212 0.02394532 0.52479787 0.88975880
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002591651 0.715391074 0.224845965
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.77180695 0.84304551 0.46564139 0.72314586 0.57170934 0.03869431
#> [7] 0.50141381 0.33929815 0.28742243 0.94920616 0.90465014 0.10452456
#> [13] 0.40781699 0.45613667 0.89700855 0.63210842 0.97123008 0.82761609
#> [19] 0.91227754 0.93450009 0.05484737 0.87393386 0.63210842 0.26439220
#> [25] 0.98563629 0.42713033 0.05484737 0.19971249 0.67417157 0.74737692
#> [31] 0.26439220 0.39814359 0.55430316 0.23871978 0.18639053 0.33929815
#> [37] 0.25178814 0.52773711 0.15903004 0.05484737 0.91227754 0.01265187
#> [43] 0.81196371 0.86623721 0.13207118 0.71501478 0.35910464 0.59793082
#> [49] 0.28742243 0.72314586 0.96390276 0.01265187 0.55430316 0.43678508
#> [55] 0.37869685 0.65746646 0.48379544 0.41746292 0.91227754 0.69092265
#> [61] 0.31844806 0.58920421 0.77994906 0.81196371 0.59793082 0.21313538
#> [67] 0.58046280 0.85080612 0.61505870 0.65746646 0.63210842 0.69092265
#> [73] 0.48379544 0.38850393 0.85080612 0.10452456 0.78801929 0.93450009
#> [79] 0.88931928 0.82761609 0.52773711 0.31844806 0.75552952 0.50141381
#> [85] 0.99281994 0.28742243 0.94920616 0.88162374 0.68258661 0.44646190
#> [91] 0.97123008 0.46564139 0.62359005 0.36891941 0.50141381 0.79602195
#> [97] 0.69092265 0.52773711 0.72314586 0.15903004 0.13207118 0.79602195
#> [103] 0.76367207 0.21313538 0.05484737 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 81 56 40 133 171 86 184 32 153 16 101 69 170
#> 14.06 12.21 18.00 14.65 16.57 23.81 17.77 20.90 21.33 8.71 9.97 23.23 19.54
#> 41 145 100 70 37 187 183 168 159 100.1 139 25 97
#> 18.02 10.07 16.07 7.38 12.52 9.92 9.24 23.72 10.55 16.07 21.49 6.32 19.14
#> 168.1 169 6 96 139.1 105 106 136 63 32.1 197 30 113
#> 23.72 22.41 15.64 14.54 21.49 19.75 16.67 21.83 22.77 20.90 21.60 17.43 22.86
#> 168.2 187.1 78 154 107 92 180 190 85 153.1 133.1 149 78.1
#> 23.72 9.92 23.88 12.63 11.18 22.92 14.82 20.81 16.44 21.33 14.65 8.37 23.88
#> 106.1 179 150 125 134 58 187.2 29 99 181 60 154.1 192
#> 16.67 18.63 20.33 15.65 17.81 19.34 9.92 15.45 21.19 16.46 13.15 12.63 16.44
#> 194 130 43 79 125.1 100.2 29.1 134.1 158 43.1 69.1 123 183.1
#> 22.40 16.47 12.10 16.23 15.65 16.07 15.45 17.81 20.14 12.10 23.23 13.00 9.24
#> 52 37.1 30.1 99.1 57 184.1 91 153.2 16.1 10 167 51 70.1
#> 10.42 12.52 17.43 21.19 14.46 17.77 5.33 21.33 8.71 10.53 15.55 18.23 7.38
#> 40.1 188 128 184.2 14 29.2 30.2 133.2 113.1 92.1 14.1 13 194.1
#> 18.00 16.16 20.35 17.77 12.89 15.45 17.43 14.65 22.86 22.92 12.89 14.34 22.40
#> 168.3 173 83 82 34 120 22 143 185 191 75 141 165
#> 23.72 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 137 62 27 191.1 147 122 141.1 182 1 1.1 151 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 138 126 191.2 172 146 112 12 146.1 72 67.1 2 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 122.1 173.1 142 87 121 74 141.2 182.1 72.1 7 75.1 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 160 116 65 126.1 87.1 87.2 132 151.1 178 11 83.1 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 126.2 48.1 120.1 65.1 12.1 172.1 17 142.1 31 196 196.1 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.2 196.2 1.2 75.2 20.1 104.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[73]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009092172 0.431488959 0.238107041
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.564203584 0.007808639 0.263149264
#> grade_iii, Cure model
#> 0.894573107
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 91 5.33 1 61 0 1
#> 24 23.89 1 38 0 0
#> 23 16.92 1 61 0 0
#> 92 22.92 1 47 0 1
#> 184 17.77 1 38 0 0
#> 100 16.07 1 60 0 0
#> 140 12.68 1 59 1 0
#> 66 22.13 1 53 0 0
#> 188 16.16 1 46 0 1
#> 100.1 16.07 1 60 0 0
#> 29 15.45 1 68 1 0
#> 110 17.56 1 65 0 1
#> 55 19.34 1 69 0 1
#> 197 21.60 1 69 1 0
#> 25 6.32 1 34 1 0
#> 99 21.19 1 38 0 1
#> 25.1 6.32 1 34 1 0
#> 123 13.00 1 44 1 0
#> 8 18.43 1 32 0 0
#> 6 15.64 1 39 0 0
#> 139 21.49 1 63 1 0
#> 128 20.35 1 35 0 1
#> 140.1 12.68 1 59 1 0
#> 111 17.45 1 47 0 1
#> 56 12.21 1 60 0 0
#> 136 21.83 1 43 0 1
#> 164 23.60 1 76 0 1
#> 117 17.46 1 26 0 1
#> 61 10.12 1 36 0 1
#> 166 19.98 1 48 0 0
#> 41 18.02 1 40 1 0
#> 4 17.64 1 NA 0 1
#> 123.1 13.00 1 44 1 0
#> 107 11.18 1 54 1 0
#> 42 12.43 1 49 0 1
#> 32 20.90 1 37 1 0
#> 139.1 21.49 1 63 1 0
#> 100.2 16.07 1 60 0 0
#> 42.1 12.43 1 49 0 1
#> 89 11.44 1 NA 0 0
#> 117.1 17.46 1 26 0 1
#> 99.1 21.19 1 38 0 1
#> 14 12.89 1 21 0 0
#> 24.1 23.89 1 38 0 0
#> 50 10.02 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 56.1 12.21 1 60 0 0
#> 14.1 12.89 1 21 0 0
#> 187 9.92 1 39 1 0
#> 99.2 21.19 1 38 0 1
#> 77 7.27 1 67 0 1
#> 154 12.63 1 20 1 0
#> 199 19.81 1 NA 0 1
#> 78 23.88 1 43 0 0
#> 159 10.55 1 50 0 1
#> 136.1 21.83 1 43 0 1
#> 86 23.81 1 58 0 1
#> 171 16.57 1 41 0 1
#> 60 13.15 1 38 1 0
#> 96 14.54 1 33 0 1
#> 157 15.10 1 47 0 0
#> 70 7.38 1 30 1 0
#> 145 10.07 1 65 1 0
#> 30 17.43 1 78 0 0
#> 181 16.46 1 45 0 1
#> 129 23.41 1 53 1 0
#> 51 18.23 1 83 0 1
#> 91.1 5.33 1 61 0 1
#> 129.1 23.41 1 53 1 0
#> 8.1 18.43 1 32 0 0
#> 124 9.73 1 NA 1 0
#> 60.1 13.15 1 38 1 0
#> 195 11.76 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 60.2 13.15 1 38 1 0
#> 39 15.59 1 37 0 1
#> 89.1 11.44 1 NA 0 0
#> 23.1 16.92 1 61 0 0
#> 149 8.37 1 33 1 0
#> 125 15.65 1 67 1 0
#> 166.1 19.98 1 48 0 0
#> 100.3 16.07 1 60 0 0
#> 166.2 19.98 1 48 0 0
#> 76 19.22 1 54 0 1
#> 195.1 11.76 1 NA 1 0
#> 164.1 23.60 1 76 0 1
#> 124.1 9.73 1 NA 1 0
#> 129.2 23.41 1 53 1 0
#> 16 8.71 1 71 0 1
#> 81 14.06 1 34 0 0
#> 157.1 15.10 1 47 0 0
#> 190 20.81 1 42 1 0
#> 101 9.97 1 10 0 1
#> 157.2 15.10 1 47 0 0
#> 145.1 10.07 1 65 1 0
#> 51.1 18.23 1 83 0 1
#> 158 20.14 1 74 1 0
#> 97 19.14 1 65 0 1
#> 50.1 10.02 1 NA 1 0
#> 70.1 7.38 1 30 1 0
#> 110.1 17.56 1 65 0 1
#> 92.1 22.92 1 47 0 1
#> 57 14.46 1 45 0 1
#> 13 14.34 1 54 0 1
#> 92.2 22.92 1 47 0 1
#> 129.3 23.41 1 53 1 0
#> 93 10.33 1 52 0 1
#> 37 12.52 1 57 1 0
#> 180 14.82 1 37 0 0
#> 105 19.75 1 60 0 0
#> 16.1 8.71 1 71 0 1
#> 175 21.91 1 43 0 0
#> 143 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 135 24.00 0 58 1 0
#> 185 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 138 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 46 24.00 0 71 0 0
#> 12 24.00 0 63 0 0
#> 21 24.00 0 47 0 0
#> 38 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 19 24.00 0 57 0 1
#> 53 24.00 0 32 0 1
#> 87 24.00 0 27 0 0
#> 73 24.00 0 NA 0 1
#> 200 24.00 0 64 0 0
#> 161 24.00 0 45 0 0
#> 161.1 24.00 0 45 0 0
#> 162 24.00 0 51 0 0
#> 156.1 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 176 24.00 0 43 0 1
#> 73.1 24.00 0 NA 0 1
#> 62 24.00 0 71 0 0
#> 172 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 17 24.00 0 38 0 1
#> 95 24.00 0 68 0 1
#> 137 24.00 0 45 1 0
#> 31 24.00 0 36 0 1
#> 137.1 24.00 0 45 1 0
#> 33 24.00 0 53 0 0
#> 53.1 24.00 0 32 0 1
#> 191 24.00 0 60 0 1
#> 12.1 24.00 0 63 0 0
#> 182 24.00 0 35 0 0
#> 19.1 24.00 0 57 0 1
#> 64.1 24.00 0 43 0 0
#> 131 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 138.1 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 20 24.00 0 46 1 0
#> 118 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 176.1 24.00 0 43 0 1
#> 75 24.00 0 21 1 0
#> 146.1 24.00 0 63 1 0
#> 53.2 24.00 0 32 0 1
#> 193 24.00 0 45 0 1
#> 98 24.00 0 34 1 0
#> 142.1 24.00 0 53 0 0
#> 87.1 24.00 0 27 0 0
#> 19.2 24.00 0 57 0 1
#> 48 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 163 24.00 0 66 0 0
#> 144 24.00 0 28 0 1
#> 121 24.00 0 57 1 0
#> 152 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 172.1 24.00 0 41 0 0
#> 121.1 24.00 0 57 1 0
#> 174 24.00 0 49 1 0
#> 95.1 24.00 0 68 0 1
#> 162.1 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 74 24.00 0 43 0 1
#> 46.1 24.00 0 71 0 0
#> 200.1 24.00 0 64 0 0
#> 27 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 35 24.00 0 51 0 0
#> 152.1 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 87.2 24.00 0 27 0 0
#> 64.2 24.00 0 43 0 0
#> 98.1 24.00 0 34 1 0
#> 7 24.00 0 37 1 0
#> 178 24.00 0 52 1 0
#> 35.1 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 20.1 24.00 0 46 1 0
#> 126 24.00 0 48 0 0
#> 3.1 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 64.3 24.00 0 43 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.564 NA NA NA
#> 2 age, Cure model 0.00781 NA NA NA
#> 3 grade_ii, Cure model 0.263 NA NA NA
#> 4 grade_iii, Cure model 0.895 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00909 NA NA NA
#> 2 grade_ii, Survival model 0.431 NA NA NA
#> 3 grade_iii, Survival model 0.238 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.564204 0.007809 0.263149 0.894573
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 250.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.564203584 0.007808639 0.263149264 0.894573107
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009092172 0.431488959 0.238107041
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.964492824 0.002381613 0.379016977 0.060465846 0.310216475 0.430516244
#> [7] 0.684937657 0.080686804 0.420091007 0.430516244 0.505156337 0.319951138
#> [13] 0.226769336 0.111722997 0.941051042 0.135848690 0.941051042 0.639668493
#> [19] 0.263025523 0.483243686 0.119855849 0.176080684 0.684937657 0.358991984
#> [25] 0.753430406 0.096242597 0.022431161 0.339472367 0.811669606 0.192741710
#> [31] 0.300570259 0.639668493 0.776567640 0.730588145 0.159539785 0.119855849
#> [37] 0.430516244 0.730588145 0.339472367 0.135848690 0.662235811 0.002381613
#> [43] 0.226769336 0.753430406 0.662235811 0.858622490 0.135848690 0.929217643
#> [49] 0.707714779 0.009781350 0.788233851 0.096242597 0.015775504 0.399366714
#> [55] 0.606080486 0.560521029 0.516164767 0.905793425 0.823419940 0.368935467
#> [61] 0.409708254 0.036480190 0.281545324 0.964492824 0.036480190 0.263025523
#> [67] 0.606080486 0.988090234 0.606080486 0.494188636 0.379016977 0.893951597
#> [73] 0.472372252 0.192741710 0.430516244 0.192741710 0.244602909 0.022431161
#> [79] 0.036480190 0.870381242 0.594613067 0.516164767 0.167820558 0.846850856
#> [85] 0.516164767 0.823419940 0.281545324 0.184370819 0.253764495 0.905793425
#> [91] 0.319951138 0.060465846 0.571844910 0.583204161 0.060465846 0.036480190
#> [97] 0.799933774 0.719143903 0.549210878 0.217891539 0.870381242 0.088353791
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 91 24 23 92 184 100 140 66 188 100.1 29 110 55
#> 5.33 23.89 16.92 22.92 17.77 16.07 12.68 22.13 16.16 16.07 15.45 17.56 19.34
#> 197 25 99 25.1 123 8 6 139 128 140.1 111 56 136
#> 21.60 6.32 21.19 6.32 13.00 18.43 15.64 21.49 20.35 12.68 17.45 12.21 21.83
#> 164 117 61 166 41 123.1 107 42 32 139.1 100.2 42.1 117.1
#> 23.60 17.46 10.12 19.98 18.02 13.00 11.18 12.43 20.90 21.49 16.07 12.43 17.46
#> 99.1 14 24.1 58 56.1 14.1 187 99.2 77 154 78 159 136.1
#> 21.19 12.89 23.89 19.34 12.21 12.89 9.92 21.19 7.27 12.63 23.88 10.55 21.83
#> 86 171 60 96 157 70 145 30 181 129 51 91.1 129.1
#> 23.81 16.57 13.15 14.54 15.10 7.38 10.07 17.43 16.46 23.41 18.23 5.33 23.41
#> 8.1 60.1 127 60.2 39 23.1 149 125 166.1 100.3 166.2 76 164.1
#> 18.43 13.15 3.53 13.15 15.59 16.92 8.37 15.65 19.98 16.07 19.98 19.22 23.60
#> 129.2 16 81 157.1 190 101 157.2 145.1 51.1 158 97 70.1 110.1
#> 23.41 8.71 14.06 15.10 20.81 9.97 15.10 10.07 18.23 20.14 19.14 7.38 17.56
#> 92.1 57 13 92.2 129.3 93 37 180 105 16.1 175 143 64
#> 22.92 14.46 14.34 22.92 23.41 10.33 12.52 14.82 19.75 8.71 21.91 24.00 24.00
#> 135 185 138 65 46 12 21 38 156 19 53 87 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 161.1 162 156.1 146 176 62 172 112 17 95 137 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 33 53.1 191 12.1 182 19.1 64.1 131 142 138.1 132 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 1 176.1 75 146.1 53.2 193 98 142.1 87.1 19.2 48 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 144 121 152 34 172.1 121.1 174 95.1 162.1 102 74 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.1 27 148 35 152.1 3 87.2 64.2 98.1 7 178 35.1 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 126 3.1 120 64.3
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[74]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001724396 0.311848082 0.249075255
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.77647817 0.01299926 0.28267146
#> grade_iii, Cure model
#> 1.03953542
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 177 12.53 1 75 0 0
#> 167 15.55 1 56 1 0
#> 15 22.68 1 48 0 0
#> 153 21.33 1 55 1 0
#> 81 14.06 1 34 0 0
#> 43 12.10 1 61 0 1
#> 77 7.27 1 67 0 1
#> 133 14.65 1 57 0 0
#> 199 19.81 1 NA 0 1
#> 153.1 21.33 1 55 1 0
#> 180 14.82 1 37 0 0
#> 10 10.53 1 34 0 0
#> 77.1 7.27 1 67 0 1
#> 155 13.08 1 26 0 0
#> 25 6.32 1 34 1 0
#> 190 20.81 1 42 1 0
#> 171 16.57 1 41 0 1
#> 171.1 16.57 1 41 0 1
#> 157 15.10 1 47 0 0
#> 86 23.81 1 58 0 1
#> 4 17.64 1 NA 0 1
#> 14 12.89 1 21 0 0
#> 42 12.43 1 49 0 1
#> 110 17.56 1 65 0 1
#> 150 20.33 1 48 0 0
#> 49 12.19 1 48 1 0
#> 123 13.00 1 44 1 0
#> 166 19.98 1 48 0 0
#> 136 21.83 1 43 0 1
#> 133.1 14.65 1 57 0 0
#> 91 5.33 1 61 0 1
#> 8 18.43 1 32 0 0
#> 184 17.77 1 38 0 0
#> 170 19.54 1 43 0 1
#> 45 17.42 1 54 0 1
#> 195 11.76 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 26 15.77 1 49 0 1
#> 168 23.72 1 70 0 0
#> 167.1 15.55 1 56 1 0
#> 10.1 10.53 1 34 0 0
#> 15.1 22.68 1 48 0 0
#> 8.1 18.43 1 32 0 0
#> 128 20.35 1 35 0 1
#> 197 21.60 1 69 1 0
#> 133.2 14.65 1 57 0 0
#> 110.1 17.56 1 65 0 1
#> 157.1 15.10 1 47 0 0
#> 195.1 11.76 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 128.1 20.35 1 35 0 1
#> 105 19.75 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 58 19.34 1 39 0 0
#> 24 23.89 1 38 0 0
#> 49.1 12.19 1 48 1 0
#> 136.1 21.83 1 43 0 1
#> 97 19.14 1 65 0 1
#> 97.1 19.14 1 65 0 1
#> 130 16.47 1 53 0 1
#> 81.1 14.06 1 34 0 0
#> 192 16.44 1 31 1 0
#> 10.2 10.53 1 34 0 0
#> 192.1 16.44 1 31 1 0
#> 190.1 20.81 1 42 1 0
#> 63 22.77 1 31 1 0
#> 40 18.00 1 28 1 0
#> 60 13.15 1 38 1 0
#> 99 21.19 1 38 0 1
#> 139 21.49 1 63 1 0
#> 181 16.46 1 45 0 1
#> 70 7.38 1 30 1 0
#> 39 15.59 1 37 0 1
#> 159 10.55 1 50 0 1
#> 153.2 21.33 1 55 1 0
#> 88 18.37 1 47 0 0
#> 14.1 12.89 1 21 0 0
#> 4.1 17.64 1 NA 0 1
#> 108 18.29 1 39 0 1
#> 171.2 16.57 1 41 0 1
#> 79 16.23 1 54 1 0
#> 113 22.86 1 34 0 0
#> 59 10.16 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 100 16.07 1 60 0 0
#> 114.1 13.68 1 NA 0 0
#> 60.1 13.15 1 38 1 0
#> 140 12.68 1 59 1 0
#> 113.1 22.86 1 34 0 0
#> 113.2 22.86 1 34 0 0
#> 61 10.12 1 36 0 1
#> 125 15.65 1 67 1 0
#> 41 18.02 1 40 1 0
#> 92 22.92 1 47 0 1
#> 60.2 13.15 1 38 1 0
#> 13 14.34 1 54 0 1
#> 49.2 12.19 1 48 1 0
#> 70.1 7.38 1 30 1 0
#> 45.1 17.42 1 54 0 1
#> 106 16.67 1 49 1 0
#> 179 18.63 1 42 0 0
#> 5 16.43 1 51 0 1
#> 32 20.90 1 37 1 0
#> 37 12.52 1 57 1 0
#> 114.2 13.68 1 NA 0 0
#> 157.2 15.10 1 47 0 0
#> 190.2 20.81 1 42 1 0
#> 16 8.71 1 71 0 1
#> 5.1 16.43 1 51 0 1
#> 183 9.24 1 67 1 0
#> 100.1 16.07 1 60 0 0
#> 43.1 12.10 1 61 0 1
#> 31 24.00 0 36 0 1
#> 31.1 24.00 0 36 0 1
#> 119 24.00 0 17 0 0
#> 176 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 83 24.00 0 6 0 0
#> 109 24.00 0 48 0 0
#> 160 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 131 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 74 24.00 0 43 0 1
#> 142.1 24.00 0 53 0 0
#> 71 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 98 24.00 0 34 1 0
#> 142.2 24.00 0 53 0 0
#> 31.2 24.00 0 36 0 1
#> 103 24.00 0 56 1 0
#> 122 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 165 24.00 0 47 0 0
#> 146 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 142.3 24.00 0 53 0 0
#> 72 24.00 0 40 0 1
#> 119.1 24.00 0 17 0 0
#> 131.1 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 82 24.00 0 34 0 0
#> 185 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 172 24.00 0 41 0 0
#> 165.1 24.00 0 47 0 0
#> 116 24.00 0 58 0 1
#> 148 24.00 0 61 1 0
#> 83.1 24.00 0 6 0 0
#> 131.2 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 156 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 72.1 24.00 0 40 0 1
#> 2 24.00 0 9 0 0
#> 137.1 24.00 0 45 1 0
#> 2.1 24.00 0 9 0 0
#> 174 24.00 0 49 1 0
#> 72.2 24.00 0 40 0 1
#> 122.1 24.00 0 66 0 0
#> 1.1 24.00 0 23 1 0
#> 62 24.00 0 71 0 0
#> 118 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 142.4 24.00 0 53 0 0
#> 98.1 24.00 0 34 1 0
#> 54 24.00 0 53 1 0
#> 12.1 24.00 0 63 0 0
#> 80.1 24.00 0 41 0 0
#> 11 24.00 0 42 0 1
#> 72.3 24.00 0 40 0 1
#> 44 24.00 0 56 0 0
#> 119.2 24.00 0 17 0 0
#> 83.2 24.00 0 6 0 0
#> 104 24.00 0 50 1 0
#> 162 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 19 24.00 0 57 0 1
#> 147 24.00 0 76 1 0
#> 118.1 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 161 24.00 0 45 0 0
#> 152 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 22 24.00 0 52 1 0
#> 161.1 24.00 0 45 0 0
#> 38 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 80.2 24.00 0 41 0 0
#> 12.2 24.00 0 63 0 0
#> 98.2 24.00 0 34 1 0
#> 160.1 24.00 0 31 1 0
#> 147.1 24.00 0 76 1 0
#> 65 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 82.1 24.00 0 34 0 0
#> 3.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.776 NA NA NA
#> 2 age, Cure model 0.0130 NA NA NA
#> 3 grade_ii, Cure model 0.283 NA NA NA
#> 4 grade_iii, Cure model 1.04 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00172 NA NA NA
#> 2 grade_ii, Survival model 0.312 NA NA NA
#> 3 grade_iii, Survival model 0.249 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.7765 0.0130 0.2827 1.0395
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 252 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.77647817 0.01299926 0.28267146 1.03953542
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001724396 0.311848082 0.249075255
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.83351104 0.67315389 0.14848432 0.22727495 0.75415269 0.87996734
#> [7] 0.97051647 0.72189347 0.22727495 0.71372172 0.90282952 0.97051647
#> [13] 0.79393839 0.98526690 0.28269045 0.54505367 0.54505367 0.68946801
#> [19] 0.03852376 0.80984360 0.84923054 0.49033393 0.34367144 0.85704312
#> [25] 0.80190967 0.35385319 0.17591069 0.72189347 0.99264507 0.42326019
#> [31] 0.48088245 0.37413553 0.51798376 0.92547819 0.64809239 0.05760497
#> [37] 0.67315389 0.90282952 0.14848432 0.42326019 0.32355898 0.20180723
#> [43] 0.72189347 0.49033393 0.68946801 0.31310215 0.32355898 0.36400975
#> [49] 0.38415783 0.01510010 0.85704312 0.17591069 0.39416200 0.39416200
#> [55] 0.57120214 0.75415269 0.58874560 0.90282952 0.58874560 0.28269045
#> [61] 0.13383467 0.47141838 0.77025306 0.26027169 0.21473822 0.57999949
#> [67] 0.95566676 0.66484460 0.89520431 0.22727495 0.44251520 0.80984360
#> [73] 0.45223174 0.54505367 0.62283241 0.09277056 0.50874899 0.63130657
#> [79] 0.77025306 0.82562239 0.09277056 0.09277056 0.93306502 0.65649699
#> [85] 0.46187123 0.07596908 0.77025306 0.74604857 0.85704312 0.95566676
#> [91] 0.51798376 0.53602855 0.41349521 0.60588504 0.27158649 0.84138941
#> [97] 0.68946801 0.28269045 0.94816149 0.60588504 0.94062941 0.63130657
#> [103] 0.87996734 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 177 167 15 153 81 43 77 133 153.1 180 10 77.1 155
#> 12.53 15.55 22.68 21.33 14.06 12.10 7.27 14.65 21.33 14.82 10.53 7.27 13.08
#> 25 190 171 171.1 157 86 14 42 110 150 49 123 166
#> 6.32 20.81 16.57 16.57 15.10 23.81 12.89 12.43 17.56 20.33 12.19 13.00 19.98
#> 136 133.1 91 8 184 170 45 52 26 168 167.1 10.1 15.1
#> 21.83 14.65 5.33 18.43 17.77 19.54 17.42 10.42 15.77 23.72 15.55 10.53 22.68
#> 8.1 128 197 133.2 110.1 157.1 68 128.1 105 58 24 49.1 136.1
#> 18.43 20.35 21.60 14.65 17.56 15.10 20.62 20.35 19.75 19.34 23.89 12.19 21.83
#> 97 97.1 130 81.1 192 10.2 192.1 190.1 63 40 60 99 139
#> 19.14 19.14 16.47 14.06 16.44 10.53 16.44 20.81 22.77 18.00 13.15 21.19 21.49
#> 181 70 39 159 153.2 88 14.1 108 171.2 79 113 117 100
#> 16.46 7.38 15.59 10.55 21.33 18.37 12.89 18.29 16.57 16.23 22.86 17.46 16.07
#> 60.1 140 113.1 113.2 61 125 41 92 60.2 13 49.2 70.1 45.1
#> 13.15 12.68 22.86 22.86 10.12 15.65 18.02 22.92 13.15 14.34 12.19 7.38 17.42
#> 106 179 5 32 37 157.2 190.2 16 5.1 183 100.1 43.1 31
#> 16.67 18.63 16.43 20.90 12.52 15.10 20.81 8.71 16.43 9.24 16.07 12.10 24.00
#> 31.1 119 176 121 186 83 109 160 142 131 12 74 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 80 98 142.2 31.2 103 122 165 146 67 142.3 72 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 1 82 185 137 172 165.1 116 148 83.1 131.2 182 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 72.1 2 137.1 2.1 174 72.2 122.1 1.1 62 118 9 142.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 54 12.1 80.1 11 72.3 44 119.2 83.2 104 162 200 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 118.1 21 161 152 3 143 144 22 161.1 38 53 80.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.2 98.2 160.1 147.1 65 35 82.1 3.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[75]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.008986111 0.828594615 0.273736770
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.91402077 0.02165257 -0.21667885
#> grade_iii, Cure model
#> 0.63121518
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 85 16.44 1 36 0 0
#> 145 10.07 1 65 1 0
#> 190 20.81 1 42 1 0
#> 69 23.23 1 25 0 1
#> 127 3.53 1 62 0 1
#> 93 10.33 1 52 0 1
#> 81 14.06 1 34 0 0
#> 10 10.53 1 34 0 0
#> 23 16.92 1 61 0 0
#> 32 20.90 1 37 1 0
#> 110 17.56 1 65 0 1
#> 81.1 14.06 1 34 0 0
#> 97 19.14 1 65 0 1
#> 16 8.71 1 71 0 1
#> 149 8.37 1 33 1 0
#> 86 23.81 1 58 0 1
#> 101 9.97 1 10 0 1
#> 16.1 8.71 1 71 0 1
#> 6 15.64 1 39 0 0
#> 159 10.55 1 50 0 1
#> 110.1 17.56 1 65 0 1
#> 52 10.42 1 52 0 1
#> 89 11.44 1 NA 0 0
#> 166 19.98 1 48 0 0
#> 107 11.18 1 54 1 0
#> 76 19.22 1 54 0 1
#> 78 23.88 1 43 0 0
#> 177 12.53 1 75 0 0
#> 188 16.16 1 46 0 1
#> 15 22.68 1 48 0 0
#> 184 17.77 1 38 0 0
#> 43 12.10 1 61 0 1
#> 194 22.40 1 38 0 1
#> 167 15.55 1 56 1 0
#> 76.1 19.22 1 54 0 1
#> 175 21.91 1 43 0 0
#> 79 16.23 1 54 1 0
#> 32.1 20.90 1 37 1 0
#> 113 22.86 1 34 0 0
#> 76.2 19.22 1 54 0 1
#> 130 16.47 1 53 0 1
#> 15.1 22.68 1 48 0 0
#> 92 22.92 1 47 0 1
#> 106 16.67 1 49 1 0
#> 183 9.24 1 67 1 0
#> 157 15.10 1 47 0 0
#> 91 5.33 1 61 0 1
#> 123 13.00 1 44 1 0
#> 123.1 13.00 1 44 1 0
#> 77 7.27 1 67 0 1
#> 195 11.76 1 NA 1 0
#> 149.1 8.37 1 33 1 0
#> 188.1 16.16 1 46 0 1
#> 78.1 23.88 1 43 0 0
#> 25 6.32 1 34 1 0
#> 111 17.45 1 47 0 1
#> 25.1 6.32 1 34 1 0
#> 180 14.82 1 37 0 0
#> 32.2 20.90 1 37 1 0
#> 30 17.43 1 78 0 0
#> 96 14.54 1 33 0 1
#> 150 20.33 1 48 0 0
#> 81.2 14.06 1 34 0 0
#> 158 20.14 1 74 1 0
#> 52.1 10.42 1 52 0 1
#> 92.1 22.92 1 47 0 1
#> 49 12.19 1 48 1 0
#> 168 23.72 1 70 0 0
#> 149.2 8.37 1 33 1 0
#> 105 19.75 1 60 0 0
#> 32.3 20.90 1 37 1 0
#> 180.1 14.82 1 37 0 0
#> 92.2 22.92 1 47 0 1
#> 86.1 23.81 1 58 0 1
#> 192 16.44 1 31 1 0
#> 91.1 5.33 1 61 0 1
#> 181 16.46 1 45 0 1
#> 107.1 11.18 1 54 1 0
#> 170 19.54 1 43 0 1
#> 180.2 14.82 1 37 0 0
#> 4 17.64 1 NA 0 1
#> 16.2 8.71 1 71 0 1
#> 45 17.42 1 54 0 1
#> 149.3 8.37 1 33 1 0
#> 5 16.43 1 51 0 1
#> 43.1 12.10 1 61 0 1
#> 124 9.73 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 99 21.19 1 38 0 1
#> 66 22.13 1 53 0 0
#> 18 15.21 1 49 1 0
#> 190.1 20.81 1 42 1 0
#> 133 14.65 1 57 0 0
#> 81.3 14.06 1 34 0 0
#> 60 13.15 1 38 1 0
#> 150.1 20.33 1 48 0 0
#> 184.1 17.77 1 38 0 0
#> 4.1 17.64 1 NA 0 1
#> 55 19.34 1 69 0 1
#> 133.1 14.65 1 57 0 0
#> 36 21.19 1 48 0 1
#> 37 12.52 1 57 1 0
#> 43.2 12.10 1 61 0 1
#> 175.1 21.91 1 43 0 0
#> 26 15.77 1 49 0 1
#> 29 15.45 1 68 1 0
#> 57 14.46 1 45 0 1
#> 149.4 8.37 1 33 1 0
#> 192.1 16.44 1 31 1 0
#> 188.2 16.16 1 46 0 1
#> 99.1 21.19 1 38 0 1
#> 181.1 16.46 1 45 0 1
#> 144 24.00 0 28 0 1
#> 38 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 21 24.00 0 47 0 0
#> 135 24.00 0 58 1 0
#> 119 24.00 0 17 0 0
#> 126 24.00 0 48 0 0
#> 67 24.00 0 25 0 0
#> 186 24.00 0 45 1 0
#> 156 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#> 34 24.00 0 36 0 0
#> 191 24.00 0 60 0 1
#> 165 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 95.1 24.00 0 68 0 1
#> 165.1 24.00 0 47 0 0
#> 182 24.00 0 35 0 0
#> 38.1 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 65 24.00 0 57 1 0
#> 176 24.00 0 43 0 1
#> 148 24.00 0 61 1 0
#> 12 24.00 0 63 0 0
#> 102 24.00 0 49 0 0
#> 109 24.00 0 48 0 0
#> 104 24.00 0 50 1 0
#> 196 24.00 0 19 0 0
#> 54 24.00 0 53 1 0
#> 115 24.00 0 NA 1 0
#> 144.1 24.00 0 28 0 1
#> 138 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 147 24.00 0 76 1 0
#> 20 24.00 0 46 1 0
#> 182.1 24.00 0 35 0 0
#> 9 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 148.1 24.00 0 61 1 0
#> 173 24.00 0 19 0 1
#> 104.1 24.00 0 50 1 0
#> 185 24.00 0 44 1 0
#> 115.1 24.00 0 NA 1 0
#> 94.1 24.00 0 51 0 1
#> 121 24.00 0 57 1 0
#> 165.2 24.00 0 47 0 0
#> 20.1 24.00 0 46 1 0
#> 193 24.00 0 45 0 1
#> 115.2 24.00 0 NA 1 0
#> 161 24.00 0 45 0 0
#> 82.1 24.00 0 34 0 0
#> 165.3 24.00 0 47 0 0
#> 146 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 47 24.00 0 38 0 1
#> 152 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 156.1 24.00 0 50 1 0
#> 84.1 24.00 0 39 0 1
#> 38.2 24.00 0 31 1 0
#> 147.1 24.00 0 76 1 0
#> 9.1 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 119.1 24.00 0 17 0 0
#> 72 24.00 0 40 0 1
#> 27 24.00 0 63 1 0
#> 132.1 24.00 0 55 0 0
#> 3 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 38.3 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 165.4 24.00 0 47 0 0
#> 173.1 24.00 0 19 0 1
#> 118.1 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#> 143 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 176.1 24.00 0 43 0 1
#> 109.1 24.00 0 48 0 0
#> 103 24.00 0 56 1 0
#> 137 24.00 0 45 1 0
#> 176.2 24.00 0 43 0 1
#> 17.1 24.00 0 38 0 1
#> 83.1 24.00 0 6 0 0
#> 131 24.00 0 66 0 0
#> 118.2 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.914 NA NA NA
#> 2 age, Cure model 0.0217 NA NA NA
#> 3 grade_ii, Cure model -0.217 NA NA NA
#> 4 grade_iii, Cure model 0.631 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00899 NA NA NA
#> 2 grade_ii, Survival model 0.829 NA NA NA
#> 3 grade_iii, Survival model 0.274 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91402 0.02165 -0.21668 0.63122
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.5
#> Residual Deviance: 251.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91402077 0.02165257 -0.21667885 0.63121518
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.008986111 0.828594615 0.273736770
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.7012481 0.9274278 0.4996785 0.2362170 0.9959383 0.9227472 0.8265751
#> [8] 0.9085966 0.6663083 0.4582778 0.6289953 0.8265751 0.6054735 0.9411623
#> [15] 0.9543971 0.1616311 0.9320362 0.9411623 0.7581352 0.9038268 0.6289953
#> [22] 0.9133574 0.5467551 0.8942589 0.5815770 0.0819263 0.8641317 0.7336009
#> [29] 0.3265814 0.6134026 0.8795177 0.3586574 0.7642466 0.5815770 0.3898594
#> [36] 0.7272563 0.4582778 0.3091854 0.5815770 0.6806335 0.3265814 0.2589271
#> [43] 0.6735683 0.9366346 0.7817797 0.9877884 0.8536799 0.8536799 0.9753503
#> [50] 0.9543971 0.7336009 0.0819263 0.9795519 0.6440802 0.9795519 0.7874803
#> [57] 0.4582778 0.6515785 0.8154736 0.5189210 0.8265751 0.5377863 0.9133574
#> [64] 0.2589271 0.8744678 0.2120063 0.9543971 0.5556453 0.4582778 0.7874803
#> [71] 0.2589271 0.1616311 0.7012481 0.9877884 0.6876178 0.8942589 0.5644350
#> [78] 0.7874803 0.9411623 0.6589902 0.9543971 0.7207575 0.8795177 0.4189938
#> [85] 0.3744566 0.7760572 0.4996785 0.8043152 0.8265751 0.8482787 0.5189210
#> [92] 0.6134026 0.5730986 0.8043152 0.4189938 0.8693431 0.8795177 0.3898594
#> [99] 0.7520030 0.7702248 0.8210425 0.9543971 0.7012481 0.7336009 0.4189938
#> [106] 0.6876178 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000
#>
#> $Time
#> 85 145 190 69 127 93 81 10 23 32 110 81.1 97
#> 16.44 10.07 20.81 23.23 3.53 10.33 14.06 10.53 16.92 20.90 17.56 14.06 19.14
#> 16 149 86 101 16.1 6 159 110.1 52 166 107 76 78
#> 8.71 8.37 23.81 9.97 8.71 15.64 10.55 17.56 10.42 19.98 11.18 19.22 23.88
#> 177 188 15 184 43 194 167 76.1 175 79 32.1 113 76.2
#> 12.53 16.16 22.68 17.77 12.10 22.40 15.55 19.22 21.91 16.23 20.90 22.86 19.22
#> 130 15.1 92 106 183 157 91 123 123.1 77 149.1 188.1 78.1
#> 16.47 22.68 22.92 16.67 9.24 15.10 5.33 13.00 13.00 7.27 8.37 16.16 23.88
#> 25 111 25.1 180 32.2 30 96 150 81.2 158 52.1 92.1 49
#> 6.32 17.45 6.32 14.82 20.90 17.43 14.54 20.33 14.06 20.14 10.42 22.92 12.19
#> 168 149.2 105 32.3 180.1 92.2 86.1 192 91.1 181 107.1 170 180.2
#> 23.72 8.37 19.75 20.90 14.82 22.92 23.81 16.44 5.33 16.46 11.18 19.54 14.82
#> 16.2 45 149.3 5 43.1 99 66 18 190.1 133 81.3 60 150.1
#> 8.71 17.42 8.37 16.43 12.10 21.19 22.13 15.21 20.81 14.65 14.06 13.15 20.33
#> 184.1 55 133.1 36 37 43.2 175.1 26 29 57 149.4 192.1 188.2
#> 17.77 19.34 14.65 21.19 12.52 12.10 21.91 15.77 15.45 14.46 8.37 16.44 16.16
#> 99.1 181.1 144 38 17 21 135 119 126 67 186 156 95
#> 21.19 16.46 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 191 165 94 95.1 165.1 182 38.1 82 65 176 148 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 109 104 196 54 144.1 138 84 147 20 182.1 9 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 173 104.1 185 94.1 121 165.2 20.1 193 161 82.1 165.3 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 47 152 132 156.1 84.1 38.2 147.1 9.1 48 119.1 72 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 3 118 71 122 38.3 7 165.4 173.1 118.1 178 143 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 109.1 103 137 176.2 17.1 83.1 131 118.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[76]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01427937 0.74069877 0.43090768
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.278694676 0.004287655 0.073015720
#> grade_iii, Cure model
#> 0.846811284
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 124 9.73 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 32 20.90 1 37 1 0
#> 52 10.42 1 52 0 1
#> 167 15.55 1 56 1 0
#> 134 17.81 1 47 1 0
#> 129 23.41 1 53 1 0
#> 111 17.45 1 47 0 1
#> 86 23.81 1 58 0 1
#> 183 9.24 1 67 1 0
#> 158 20.14 1 74 1 0
#> 66 22.13 1 53 0 0
#> 37 12.52 1 57 1 0
#> 158.1 20.14 1 74 1 0
#> 24 23.89 1 38 0 0
#> 108 18.29 1 39 0 1
#> 101 9.97 1 10 0 1
#> 153 21.33 1 55 1 0
#> 105 19.75 1 60 0 0
#> 37.1 12.52 1 57 1 0
#> 78 23.88 1 43 0 0
#> 136.1 21.83 1 43 0 1
#> 170 19.54 1 43 0 1
#> 30 17.43 1 78 0 0
#> 154 12.63 1 20 1 0
#> 171 16.57 1 41 0 1
#> 30.1 17.43 1 78 0 0
#> 150 20.33 1 48 0 0
#> 85 16.44 1 36 0 0
#> 158.2 20.14 1 74 1 0
#> 105.1 19.75 1 60 0 0
#> 155 13.08 1 26 0 0
#> 149 8.37 1 33 1 0
#> 110 17.56 1 65 0 1
#> 5 16.43 1 51 0 1
#> 25 6.32 1 34 1 0
#> 171.1 16.57 1 41 0 1
#> 175 21.91 1 43 0 0
#> 170.1 19.54 1 43 0 1
#> 39 15.59 1 37 0 1
#> 150.1 20.33 1 48 0 0
#> 57 14.46 1 45 0 1
#> 169 22.41 1 46 0 0
#> 100 16.07 1 60 0 0
#> 169.1 22.41 1 46 0 0
#> 14 12.89 1 21 0 0
#> 41 18.02 1 40 1 0
#> 155.1 13.08 1 26 0 0
#> 105.2 19.75 1 60 0 0
#> 133 14.65 1 57 0 0
#> 110.1 17.56 1 65 0 1
#> 56 12.21 1 60 0 0
#> 4 17.64 1 NA 0 1
#> 113 22.86 1 34 0 0
#> 145 10.07 1 65 1 0
#> 110.2 17.56 1 65 0 1
#> 127 3.53 1 62 0 1
#> 181 16.46 1 45 0 1
#> 4.1 17.64 1 NA 0 1
#> 153.1 21.33 1 55 1 0
#> 79 16.23 1 54 1 0
#> 61 10.12 1 36 0 1
#> 90 20.94 1 50 0 1
#> 171.2 16.57 1 41 0 1
#> 57.1 14.46 1 45 0 1
#> 36 21.19 1 48 0 1
#> 188 16.16 1 46 0 1
#> 124.1 9.73 1 NA 1 0
#> 79.1 16.23 1 54 1 0
#> 168 23.72 1 70 0 0
#> 107 11.18 1 54 1 0
#> 194 22.40 1 38 0 1
#> 6 15.64 1 39 0 0
#> 187 9.92 1 39 1 0
#> 111.1 17.45 1 47 0 1
#> 197 21.60 1 69 1 0
#> 155.2 13.08 1 26 0 0
#> 167.1 15.55 1 56 1 0
#> 105.3 19.75 1 60 0 0
#> 4.2 17.64 1 NA 0 1
#> 177 12.53 1 75 0 0
#> 189 10.51 1 NA 1 0
#> 158.3 20.14 1 74 1 0
#> 157 15.10 1 47 0 0
#> 43 12.10 1 61 0 1
#> 25.1 6.32 1 34 1 0
#> 51 18.23 1 83 0 1
#> 93 10.33 1 52 0 1
#> 60 13.15 1 38 1 0
#> 45 17.42 1 54 0 1
#> 192 16.44 1 31 1 0
#> 170.2 19.54 1 43 0 1
#> 45.1 17.42 1 54 0 1
#> 179 18.63 1 42 0 0
#> 166 19.98 1 48 0 0
#> 107.1 11.18 1 54 1 0
#> 184 17.77 1 38 0 0
#> 8 18.43 1 32 0 0
#> 26 15.77 1 49 0 1
#> 5.1 16.43 1 51 0 1
#> 79.2 16.23 1 54 1 0
#> 59 10.16 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 140 12.68 1 59 1 0
#> 49 12.19 1 48 1 0
#> 149.1 8.37 1 33 1 0
#> 56.1 12.21 1 60 0 0
#> 164 23.60 1 76 0 1
#> 32.1 20.90 1 37 1 0
#> 133.1 14.65 1 57 0 0
#> 66.1 22.13 1 53 0 0
#> 50 10.02 1 NA 1 0
#> 75 24.00 0 21 1 0
#> 198 24.00 0 66 0 1
#> 160 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 172 24.00 0 41 0 0
#> 135 24.00 0 58 1 0
#> 11 24.00 0 42 0 1
#> 3 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 165 24.00 0 47 0 0
#> 109 24.00 0 48 0 0
#> 143 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 132 24.00 0 55 0 0
#> 126 24.00 0 48 0 0
#> 163 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 98 24.00 0 34 1 0
#> 172.1 24.00 0 41 0 0
#> 33 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 46 24.00 0 71 0 0
#> 151 24.00 0 42 0 0
#> 87 24.00 0 27 0 0
#> 46.1 24.00 0 71 0 0
#> 103 24.00 0 56 1 0
#> 161 24.00 0 45 0 0
#> 172.2 24.00 0 41 0 0
#> 46.2 24.00 0 71 0 0
#> 109.1 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 115 24.00 0 NA 1 0
#> 126.1 24.00 0 48 0 0
#> 165.1 24.00 0 47 0 0
#> 191 24.00 0 60 0 1
#> 1 24.00 0 23 1 0
#> 47 24.00 0 38 0 1
#> 137 24.00 0 45 1 0
#> 102 24.00 0 49 0 0
#> 82 24.00 0 34 0 0
#> 118 24.00 0 44 1 0
#> 19.1 24.00 0 57 0 1
#> 21 24.00 0 47 0 0
#> 44.1 24.00 0 56 0 0
#> 75.2 24.00 0 21 1 0
#> 72 24.00 0 40 0 1
#> 74 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 20 24.00 0 46 1 0
#> 146.1 24.00 0 63 1 0
#> 186 24.00 0 45 1 0
#> 3.1 24.00 0 31 1 0
#> 109.2 24.00 0 48 0 0
#> 121 24.00 0 57 1 0
#> 132.1 24.00 0 55 0 0
#> 74.1 24.00 0 43 0 1
#> 62 24.00 0 71 0 0
#> 12 24.00 0 63 0 0
#> 62.1 24.00 0 71 0 0
#> 137.1 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 131 24.00 0 66 0 0
#> 47.1 24.00 0 38 0 1
#> 146.2 24.00 0 63 1 0
#> 9 24.00 0 31 1 0
#> 17.1 24.00 0 38 0 1
#> 141.1 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 121.1 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 122 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 156 24.00 0 50 1 0
#> 156.1 24.00 0 50 1 0
#> 163.1 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 65 24.00 0 57 1 0
#> 62.2 24.00 0 71 0 0
#> 118.1 24.00 0 44 1 0
#> 198.1 24.00 0 66 0 1
#> 72.1 24.00 0 40 0 1
#> 84.1 24.00 0 39 0 1
#> 104 24.00 0 50 1 0
#> 143.1 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.279 NA NA NA
#> 2 age, Cure model 0.00429 NA NA NA
#> 3 grade_ii, Cure model 0.0730 NA NA NA
#> 4 grade_iii, Cure model 0.847 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0143 NA NA NA
#> 2 grade_ii, Survival model 0.741 NA NA NA
#> 3 grade_iii, Survival model 0.431 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.278695 0.004288 0.073016 0.846811
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 255.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.278694676 0.004287655 0.073015720 0.846811284
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01427937 0.74069877 0.43090768
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0550521929 0.1033492942 0.8498970843 0.5732016557 0.2853762570
#> [6] 0.0128757340 0.3342942149 0.0031991406 0.9255074529 0.1316165110
#> [11] 0.0365477422 0.7511674929 0.1316165110 0.0002349067 0.2564234802
#> [16] 0.9003492939 0.0752348577 0.1688340240 0.7511674929 0.0013125015
#> [21] 0.0550521929 0.2021975810 0.3545132041 0.7269017558 0.3969074495
#> [26] 0.3545132041 0.1170594557 0.4398845018 0.1316165110 0.1688340240
#> [31] 0.6668477550 0.9381022611 0.3048043832 0.4616230589 0.9629181259
#> [36] 0.3969074495 0.0483412787 0.2021975810 0.5616977375 0.1170594557
#> [41] 0.6312131035 0.0213625531 0.5275107136 0.0213625531 0.7025538906
#> [46] 0.2757056523 0.6668477550 0.1688340240 0.6076666009 0.3048043832
#> [51] 0.7754213093 0.0169131602 0.8876936106 0.3048043832 0.9875494902
#> [56] 0.4288926745 0.0752348577 0.4836282953 0.8750686972 0.0960135705
#> [61] 0.3969074495 0.6312131035 0.0888136576 0.5163246250 0.4836282953
#> [66] 0.0055852506 0.8250578633 0.0311143127 0.5502156574 0.9129458581
#> [71] 0.3342942149 0.0681699979 0.6668477550 0.5732016557 0.1688340240
#> [76] 0.7389691549 0.1316165110 0.5960306528 0.8125547231 0.9629181259
#> [81] 0.2659720160 0.8624583025 0.6549284518 0.3755377209 0.4398845018
#> [86] 0.2021975810 0.3755377209 0.2375426952 0.1607895517 0.8250578633
#> [91] 0.2950233426 0.2469168848 0.5388349962 0.4616230589 0.4836282953
#> [96] 0.2283324689 0.7147177872 0.8001197130 0.9381022611 0.7754213093
#> [101] 0.0088688056 0.1033492942 0.6076666009 0.0365477422 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 136 32 52 167 134 129 111 86 183 158 66 37 158.1
#> 21.83 20.90 10.42 15.55 17.81 23.41 17.45 23.81 9.24 20.14 22.13 12.52 20.14
#> 24 108 101 153 105 37.1 78 136.1 170 30 154 171 30.1
#> 23.89 18.29 9.97 21.33 19.75 12.52 23.88 21.83 19.54 17.43 12.63 16.57 17.43
#> 150 85 158.2 105.1 155 149 110 5 25 171.1 175 170.1 39
#> 20.33 16.44 20.14 19.75 13.08 8.37 17.56 16.43 6.32 16.57 21.91 19.54 15.59
#> 150.1 57 169 100 169.1 14 41 155.1 105.2 133 110.1 56 113
#> 20.33 14.46 22.41 16.07 22.41 12.89 18.02 13.08 19.75 14.65 17.56 12.21 22.86
#> 145 110.2 127 181 153.1 79 61 90 171.2 57.1 36 188 79.1
#> 10.07 17.56 3.53 16.46 21.33 16.23 10.12 20.94 16.57 14.46 21.19 16.16 16.23
#> 168 107 194 6 187 111.1 197 155.2 167.1 105.3 177 158.3 157
#> 23.72 11.18 22.40 15.64 9.92 17.45 21.60 13.08 15.55 19.75 12.53 20.14 15.10
#> 43 25.1 51 93 60 45 192 170.2 45.1 179 166 107.1 184
#> 12.10 6.32 18.23 10.33 13.15 17.42 16.44 19.54 17.42 18.63 19.98 11.18 17.77
#> 8 26 5.1 79.2 97 140 49 149.1 56.1 164 32.1 133.1 66.1
#> 18.43 15.77 16.43 16.23 19.14 12.68 12.19 8.37 12.21 23.60 20.90 14.65 22.13
#> 75 198 160 141 44 172 135 11 3 165 109 143 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 126 163 19 98 172.1 33 38 75.1 46 151 87 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 161 172.2 46.2 109.1 147 126.1 165.1 191 1 47 137 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 118 19.1 21 44.1 75.2 72 74 146 17 20 146.1 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 109.2 121 132.1 74.1 62 12 62.1 137.1 48 142 131 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146.2 9 17.1 141.1 103.1 121.1 148 122 84 156 156.1 163.1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 62.2 118.1 198.1 72.1 84.1 104 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[77]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001319729 0.298182360 0.360598550
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.74423482 0.01650688 -0.43930622
#> grade_iii, Cure model
#> 1.58094391
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 36 21.19 1 48 0 1
#> 66 22.13 1 53 0 0
#> 139 21.49 1 63 1 0
#> 45 17.42 1 54 0 1
#> 40 18.00 1 28 1 0
#> 93 10.33 1 52 0 1
#> 79 16.23 1 54 1 0
#> 167 15.55 1 56 1 0
#> 184 17.77 1 38 0 0
#> 153 21.33 1 55 1 0
#> 177 12.53 1 75 0 0
#> 81 14.06 1 34 0 0
#> 117 17.46 1 26 0 1
#> 154 12.63 1 20 1 0
#> 164 23.60 1 76 0 1
#> 129 23.41 1 53 1 0
#> 30 17.43 1 78 0 0
#> 123 13.00 1 44 1 0
#> 150 20.33 1 48 0 0
#> 197 21.60 1 69 1 0
#> 197.1 21.60 1 69 1 0
#> 76 19.22 1 54 0 1
#> 155 13.08 1 26 0 0
#> 32 20.90 1 37 1 0
#> 24 23.89 1 38 0 0
#> 92 22.92 1 47 0 1
#> 113 22.86 1 34 0 0
#> 157 15.10 1 47 0 0
#> 14 12.89 1 21 0 0
#> 91 5.33 1 61 0 1
#> 180 14.82 1 37 0 0
#> 139.1 21.49 1 63 1 0
#> 157.1 15.10 1 47 0 0
#> 192 16.44 1 31 1 0
#> 26 15.77 1 49 0 1
#> 194 22.40 1 38 0 1
#> 26.1 15.77 1 49 0 1
#> 91.1 5.33 1 61 0 1
#> 45.1 17.42 1 54 0 1
#> 140 12.68 1 59 1 0
#> 105 19.75 1 60 0 0
#> 90 20.94 1 50 0 1
#> 45.2 17.42 1 54 0 1
#> 6 15.64 1 39 0 0
#> 110 17.56 1 65 0 1
#> 78 23.88 1 43 0 0
#> 111 17.45 1 47 0 1
#> 23 16.92 1 61 0 0
#> 136 21.83 1 43 0 1
#> 56 12.21 1 60 0 0
#> 117.1 17.46 1 26 0 1
#> 69 23.23 1 25 0 1
#> 177.1 12.53 1 75 0 0
#> 78.1 23.88 1 43 0 0
#> 145 10.07 1 65 1 0
#> 86 23.81 1 58 0 1
#> 188 16.16 1 46 0 1
#> 43 12.10 1 61 0 1
#> 13 14.34 1 54 0 1
#> 39 15.59 1 37 0 1
#> 107 11.18 1 54 1 0
#> 79.1 16.23 1 54 1 0
#> 14.1 12.89 1 21 0 0
#> 179 18.63 1 42 0 0
#> 197.2 21.60 1 69 1 0
#> 13.1 14.34 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 183 9.24 1 67 1 0
#> 58 19.34 1 39 0 0
#> 50 10.02 1 NA 1 0
#> 66.1 22.13 1 53 0 0
#> 113.1 22.86 1 34 0 0
#> 139.2 21.49 1 63 1 0
#> 169 22.41 1 46 0 0
#> 61 10.12 1 36 0 1
#> 188.1 16.16 1 46 0 1
#> 88 18.37 1 47 0 0
#> 15 22.68 1 48 0 0
#> 125 15.65 1 67 1 0
#> 123.1 13.00 1 44 1 0
#> 125.1 15.65 1 67 1 0
#> 175 21.91 1 43 0 0
#> 23.1 16.92 1 61 0 0
#> 117.2 17.46 1 26 0 1
#> 26.2 15.77 1 49 0 1
#> 13.2 14.34 1 54 0 1
#> 97 19.14 1 65 0 1
#> 36.1 21.19 1 48 0 1
#> 91.2 5.33 1 61 0 1
#> 5 16.43 1 51 0 1
#> 101 9.97 1 10 0 1
#> 42 12.43 1 49 0 1
#> 99 21.19 1 38 0 1
#> 101.1 9.97 1 10 0 1
#> 199 19.81 1 NA 0 1
#> 108 18.29 1 39 0 1
#> 159 10.55 1 50 0 1
#> 36.2 21.19 1 48 0 1
#> 114 13.68 1 NA 0 0
#> 113.2 22.86 1 34 0 0
#> 6.1 15.64 1 39 0 0
#> 51 18.23 1 83 0 1
#> 197.3 21.60 1 69 1 0
#> 59 10.16 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 69.1 23.23 1 25 0 1
#> 60 13.15 1 38 1 0
#> 23.2 16.92 1 61 0 0
#> 88.1 18.37 1 47 0 0
#> 129.1 23.41 1 53 1 0
#> 23.3 16.92 1 61 0 0
#> 125.2 15.65 1 67 1 0
#> 33 24.00 0 53 0 0
#> 143 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 160 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 73 24.00 0 NA 0 1
#> 141 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 67 24.00 0 25 0 0
#> 98 24.00 0 34 1 0
#> 176.1 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 186 24.00 0 45 1 0
#> 87 24.00 0 27 0 0
#> 135.1 24.00 0 58 1 0
#> 112 24.00 0 61 0 0
#> 46 24.00 0 71 0 0
#> 186.1 24.00 0 45 1 0
#> 2 24.00 0 9 0 0
#> 162 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 73.1 24.00 0 NA 0 1
#> 3 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 196 24.00 0 19 0 0
#> 27.1 24.00 0 63 1 0
#> 38 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 46.1 24.00 0 71 0 0
#> 178 24.00 0 52 1 0
#> 141.1 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 28 24.00 0 67 1 0
#> 102 24.00 0 49 0 0
#> 121 24.00 0 57 1 0
#> 185.1 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 118 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 48 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 115 24.00 0 NA 1 0
#> 143.1 24.00 0 51 0 0
#> 46.2 24.00 0 71 0 0
#> 132 24.00 0 55 0 0
#> 147 24.00 0 76 1 0
#> 115.1 24.00 0 NA 1 0
#> 71 24.00 0 51 0 0
#> 82.1 24.00 0 34 0 0
#> 44 24.00 0 56 0 0
#> 83.1 24.00 0 6 0 0
#> 185.2 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 7 24.00 0 37 1 0
#> 185.3 24.00 0 44 1 0
#> 160.2 24.00 0 31 1 0
#> 7.1 24.00 0 37 1 0
#> 64 24.00 0 43 0 0
#> 19 24.00 0 57 0 1
#> 115.2 24.00 0 NA 1 0
#> 22 24.00 0 52 1 0
#> 74.1 24.00 0 43 0 1
#> 122 24.00 0 66 0 0
#> 163.1 24.00 0 66 0 0
#> 126 24.00 0 48 0 0
#> 21 24.00 0 47 0 0
#> 104 24.00 0 50 1 0
#> 151 24.00 0 42 0 0
#> 142 24.00 0 53 0 0
#> 38.1 24.00 0 31 1 0
#> 2.1 24.00 0 9 0 0
#> 120 24.00 0 68 0 1
#> 147.1 24.00 0 76 1 0
#> 73.2 24.00 0 NA 0 1
#> 2.2 24.00 0 9 0 0
#> 185.4 24.00 0 44 1 0
#> 174.1 24.00 0 49 1 0
#> 54 24.00 0 53 1 0
#> 64.1 24.00 0 43 0 0
#> 44.1 24.00 0 56 0 0
#> 148 24.00 0 61 1 0
#> 87.1 24.00 0 27 0 0
#> 19.1 24.00 0 57 0 1
#> 148.1 24.00 0 61 1 0
#> 102.1 24.00 0 49 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.744 NA NA NA
#> 2 age, Cure model 0.0165 NA NA NA
#> 3 grade_ii, Cure model -0.439 NA NA NA
#> 4 grade_iii, Cure model 1.58 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00132 NA NA NA
#> 2 grade_ii, Survival model 0.298 NA NA NA
#> 3 grade_iii, Survival model 0.361 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74423 0.01651 -0.43931 1.58094
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 258.7
#> Residual Deviance: 231.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74423482 0.01650688 -0.43930622 1.58094391
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001319729 0.298182360 0.360598550
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.37573950 0.24915368 0.33604402 0.58966408 0.52154675 0.93041967
#> [7] 0.66220909 0.76208820 0.53031826 0.36569960 0.88005251 0.81417568
#> [13] 0.54776695 0.87278602 0.09637799 0.11295146 0.58125954 0.83634142
#> [19] 0.43099416 0.29546360 0.29546360 0.45874125 0.82896361 0.42171808
#> [25] 0.01602094 0.16551422 0.17806394 0.76962890 0.85092235 0.97953421
#> [31] 0.78461774 0.33604402 0.76962890 0.64601464 0.69375836 0.23726673
#> [37] 0.69375836 0.97953421 0.58966408 0.86549626 0.44025722 0.41235658
#> [43] 0.58966408 0.73936422 0.53908232 0.04147056 0.57284181 0.61396695
#> [49] 0.28395834 0.90172327 0.54776695 0.14040594 0.88005251 0.04147056
#> [55] 0.94459743 0.07796465 0.67807984 0.90894101 0.79214468 0.75451371
#> [61] 0.91612711 0.66220909 0.85092235 0.47691721 0.29546360 0.79214468
#> [67] 0.96560378 0.44950425 0.24915368 0.17806394 0.33604402 0.22506959
#> [73] 0.93752206 0.67807984 0.48594579 0.21283111 0.71673244 0.83634142
#> [79] 0.71673244 0.27220656 0.61396695 0.54776695 0.69375836 0.79214468
#> [85] 0.46787889 0.37573950 0.97953421 0.65413863 0.95164808 0.89450077
#> [91] 0.37573950 0.95164808 0.50379324 0.92328810 0.37573950 0.17806394
#> [97] 0.73936422 0.51271611 0.29546360 0.97258313 0.14040594 0.82158351
#> [103] 0.61396695 0.48594579 0.11295146 0.61396695 0.71673244 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 36 66 139 45 40 93 79 167 184 153 177 81 117
#> 21.19 22.13 21.49 17.42 18.00 10.33 16.23 15.55 17.77 21.33 12.53 14.06 17.46
#> 154 164 129 30 123 150 197 197.1 76 155 32 24 92
#> 12.63 23.60 23.41 17.43 13.00 20.33 21.60 21.60 19.22 13.08 20.90 23.89 22.92
#> 113 157 14 91 180 139.1 157.1 192 26 194 26.1 91.1 45.1
#> 22.86 15.10 12.89 5.33 14.82 21.49 15.10 16.44 15.77 22.40 15.77 5.33 17.42
#> 140 105 90 45.2 6 110 78 111 23 136 56 117.1 69
#> 12.68 19.75 20.94 17.42 15.64 17.56 23.88 17.45 16.92 21.83 12.21 17.46 23.23
#> 177.1 78.1 145 86 188 43 13 39 107 79.1 14.1 179 197.2
#> 12.53 23.88 10.07 23.81 16.16 12.10 14.34 15.59 11.18 16.23 12.89 18.63 21.60
#> 13.1 183 58 66.1 113.1 139.2 169 61 188.1 88 15 125 123.1
#> 14.34 9.24 19.34 22.13 22.86 21.49 22.41 10.12 16.16 18.37 22.68 15.65 13.00
#> 125.1 175 23.1 117.2 26.2 13.2 97 36.1 91.2 5 101 42 99
#> 15.65 21.91 16.92 17.46 15.77 14.34 19.14 21.19 5.33 16.43 9.97 12.43 21.19
#> 101.1 108 159 36.2 113.2 6.1 51 197.3 77 69.1 60 23.2 88.1
#> 9.97 18.29 10.55 21.19 22.86 15.64 18.23 21.60 7.27 23.23 13.15 16.92 18.37
#> 129.1 23.3 125.2 33 143 176 27 160 135 141 161 67 98
#> 23.41 16.92 15.65 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 185 94 186 87 135.1 112 46 186.1 2 162 137 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 196 27.1 38 160.1 163 46.1 178 141.1 47 28 102 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 82 118 83 48 74 143.1 46.2 132 147 71 82.1 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83.1 185.2 146 7 185.3 160.2 7.1 64 19 22 74.1 122 163.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 21 104 151 142 38.1 2.1 120 147.1 2.2 185.4 174.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.1 44.1 148 87.1 19.1 148.1 102.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[78]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.000560114 0.647782058 0.440785727
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.28740118 0.02677387 -0.11922841
#> grade_iii, Cure model
#> 0.50684620
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 91 5.33 1 61 0 1
#> 91.1 5.33 1 61 0 1
#> 113 22.86 1 34 0 0
#> 108 18.29 1 39 0 1
#> 153 21.33 1 55 1 0
#> 114 13.68 1 NA 0 0
#> 167 15.55 1 56 1 0
#> 50 10.02 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 51 18.23 1 83 0 1
#> 16 8.71 1 71 0 1
#> 39 15.59 1 37 0 1
#> 81 14.06 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 167.1 15.55 1 56 1 0
#> 183 9.24 1 67 1 0
#> 52 10.42 1 52 0 1
#> 181 16.46 1 45 0 1
#> 154 12.63 1 20 1 0
#> 149 8.37 1 33 1 0
#> 13 14.34 1 54 0 1
#> 93 10.33 1 52 0 1
#> 26 15.77 1 49 0 1
#> 127 3.53 1 62 0 1
#> 105 19.75 1 60 0 0
#> 56 12.21 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 164 23.60 1 76 0 1
#> 66 22.13 1 53 0 0
#> 91.2 5.33 1 61 0 1
#> 37 12.52 1 57 1 0
#> 13.1 14.34 1 54 0 1
#> 125 15.65 1 67 1 0
#> 123 13.00 1 44 1 0
#> 13.2 14.34 1 54 0 1
#> 4.1 17.64 1 NA 0 1
#> 76 19.22 1 54 0 1
#> 58 19.34 1 39 0 0
#> 188 16.16 1 46 0 1
#> 159 10.55 1 50 0 1
#> 29 15.45 1 68 1 0
#> 179 18.63 1 42 0 0
#> 23 16.92 1 61 0 0
#> 117 17.46 1 26 0 1
#> 184 17.77 1 38 0 0
#> 16.1 8.71 1 71 0 1
#> 154.1 12.63 1 20 1 0
#> 32 20.90 1 37 1 0
#> 107 11.18 1 54 1 0
#> 10 10.53 1 34 0 0
#> 124 9.73 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 167.2 15.55 1 56 1 0
#> 99 21.19 1 38 0 1
#> 145 10.07 1 65 1 0
#> 23.1 16.92 1 61 0 0
#> 190 20.81 1 42 1 0
#> 139 21.49 1 63 1 0
#> 180 14.82 1 37 0 0
#> 124.1 9.73 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 78 23.88 1 43 0 0
#> 150.1 20.33 1 48 0 0
#> 24 23.89 1 38 0 0
#> 145.1 10.07 1 65 1 0
#> 117.1 17.46 1 26 0 1
#> 108.1 18.29 1 39 0 1
#> 23.2 16.92 1 61 0 0
#> 188.1 16.16 1 46 0 1
#> 167.3 15.55 1 56 1 0
#> 140 12.68 1 59 1 0
#> 136.1 21.83 1 43 0 1
#> 16.2 8.71 1 71 0 1
#> 4.2 17.64 1 NA 0 1
#> 5 16.43 1 51 0 1
#> 164.1 23.60 1 76 0 1
#> 99.1 21.19 1 38 0 1
#> 39.1 15.59 1 37 0 1
#> 184.1 17.77 1 38 0 0
#> 99.2 21.19 1 38 0 1
#> 52.1 10.42 1 52 0 1
#> 140.1 12.68 1 59 1 0
#> 197 21.60 1 69 1 0
#> 29.1 15.45 1 68 1 0
#> 32.1 20.90 1 37 1 0
#> 92 22.92 1 47 0 1
#> 199 19.81 1 NA 0 1
#> 188.2 16.16 1 46 0 1
#> 140.2 12.68 1 59 1 0
#> 110 17.56 1 65 0 1
#> 51.1 18.23 1 83 0 1
#> 111 17.45 1 47 0 1
#> 139.1 21.49 1 63 1 0
#> 199.1 19.81 1 NA 0 1
#> 85 16.44 1 36 0 0
#> 4.3 17.64 1 NA 0 1
#> 90 20.94 1 50 0 1
#> 154.2 12.63 1 20 1 0
#> 140.3 12.68 1 59 1 0
#> 79 16.23 1 54 1 0
#> 61 10.12 1 36 0 1
#> 76.1 19.22 1 54 0 1
#> 170 19.54 1 43 0 1
#> 51.2 18.23 1 83 0 1
#> 171 16.57 1 41 0 1
#> 129 23.41 1 53 1 0
#> 88 18.37 1 47 0 0
#> 56.1 12.21 1 60 0 0
#> 15 22.68 1 48 0 0
#> 130 16.47 1 53 0 1
#> 177 12.53 1 75 0 0
#> 178 24.00 0 52 1 0
#> 72 24.00 0 40 0 1
#> 198 24.00 0 66 0 1
#> 82 24.00 0 34 0 0
#> 144 24.00 0 28 0 1
#> 120 24.00 0 68 0 1
#> 12 24.00 0 63 0 0
#> 176 24.00 0 43 0 1
#> 109 24.00 0 48 0 0
#> 144.1 24.00 0 28 0 1
#> 19 24.00 0 57 0 1
#> 7 24.00 0 37 1 0
#> 147 24.00 0 76 1 0
#> 7.1 24.00 0 37 1 0
#> 185 24.00 0 44 1 0
#> 7.2 24.00 0 37 1 0
#> 160 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 104 24.00 0 50 1 0
#> 147.1 24.00 0 76 1 0
#> 104.1 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 54 24.00 0 53 1 0
#> 3 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 104.2 24.00 0 50 1 0
#> 9.1 24.00 0 31 1 0
#> 120.1 24.00 0 68 0 1
#> 122 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 54.1 24.00 0 53 1 0
#> 9.2 24.00 0 31 1 0
#> 12.1 24.00 0 63 0 0
#> 138 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 94 24.00 0 51 0 1
#> 73 24.00 0 NA 0 1
#> 173 24.00 0 19 0 1
#> 116.1 24.00 0 58 0 1
#> 54.2 24.00 0 53 1 0
#> 120.2 24.00 0 68 0 1
#> 152 24.00 0 36 0 1
#> 151 24.00 0 42 0 0
#> 47 24.00 0 38 0 1
#> 119 24.00 0 17 0 0
#> 19.1 24.00 0 57 0 1
#> 119.1 24.00 0 17 0 0
#> 191 24.00 0 60 0 1
#> 193 24.00 0 45 0 1
#> 3.1 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 119.2 24.00 0 17 0 0
#> 174 24.00 0 49 1 0
#> 138.1 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 19.2 24.00 0 57 0 1
#> 1 24.00 0 23 1 0
#> 53 24.00 0 32 0 1
#> 126 24.00 0 48 0 0
#> 3.2 24.00 0 31 1 0
#> 94.1 24.00 0 51 0 1
#> 135 24.00 0 58 1 0
#> 173.1 24.00 0 19 0 1
#> 143 24.00 0 51 0 0
#> 71.1 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 9.3 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 120.3 24.00 0 68 0 1
#> 71.2 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 146 24.00 0 63 1 0
#> 120.4 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 132 24.00 0 55 0 0
#> 119.3 24.00 0 17 0 0
#> 137 24.00 0 45 1 0
#> 173.2 24.00 0 19 0 1
#> 161 24.00 0 45 0 0
#> 182 24.00 0 35 0 0
#> 193.1 24.00 0 45 0 1
#> 142 24.00 0 53 0 0
#> 185.1 24.00 0 44 1 0
#> 104.3 24.00 0 50 1 0
#> 34.1 24.00 0 36 0 0
#> 46 24.00 0 71 0 0
#> 44 24.00 0 56 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.29 NA NA NA
#> 2 age, Cure model 0.0268 NA NA NA
#> 3 grade_ii, Cure model -0.119 NA NA NA
#> 4 grade_iii, Cure model 0.507 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000560 NA NA NA
#> 2 grade_ii, Survival model 0.648 NA NA NA
#> 3 grade_iii, Survival model 0.441 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.28740 0.02677 -0.11923 0.50685
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 246.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.28740118 0.02677387 -0.11922841 0.50684620
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.000560114 0.647782058 0.440785727
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.97495514 0.97495514 0.15745388 0.47349001 0.29378627 0.71813037
#> [7] 0.57468003 0.49265341 0.94947044 0.70222807 0.79265879 0.71813037
#> [13] 0.94297544 0.90332354 0.62718462 0.83520403 0.96858216 0.77074331
#> [19] 0.91665157 0.68592397 0.99372707 0.40319167 0.86943480 0.38269379
#> [25] 0.08395198 0.20768522 0.97495514 0.86259937 0.77074331 0.69412314
#> [31] 0.80003101 0.77074331 0.43400333 0.42378697 0.66144668 0.88982511
#> [37] 0.74829867 0.45364598 0.58354863 0.54779900 0.52012138 0.94947044
#> [43] 0.83520403 0.35121336 0.88304464 0.89657481 0.19098050 0.71813037
#> [49] 0.30625569 0.92994210 0.58354863 0.37228855 0.26835142 0.76323819
#> [55] 0.22435030 0.05149373 0.38269379 0.01934665 0.92994210 0.54779900
#> [61] 0.47349001 0.58354863 0.66144668 0.71813037 0.80733865 0.22435030
#> [67] 0.94947044 0.64443916 0.08395198 0.30625569 0.70222807 0.52012138
#> [73] 0.30625569 0.90332354 0.80733865 0.25394770 0.74829867 0.35121336
#> [79] 0.14063651 0.66144668 0.80733865 0.53858441 0.49265341 0.56572832
#> [85] 0.26835142 0.63581308 0.33985457 0.83520403 0.80733865 0.65299663
#> [91] 0.92331084 0.43400333 0.41356517 0.49265341 0.60971150 0.12253486
#> [97] 0.46357083 0.86943480 0.17423852 0.61848513 0.85571081 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 91 91.1 113 108 153 167 45 51 16 39 81 167.1 183
#> 5.33 5.33 22.86 18.29 21.33 15.55 17.42 18.23 8.71 15.59 14.06 15.55 9.24
#> 52 181 154 149 13 93 26 127 105 56 150 164 66
#> 10.42 16.46 12.63 8.37 14.34 10.33 15.77 3.53 19.75 12.21 20.33 23.60 22.13
#> 91.2 37 13.1 125 123 13.2 76 58 188 159 29 179 23
#> 5.33 12.52 14.34 15.65 13.00 14.34 19.22 19.34 16.16 10.55 15.45 18.63 16.92
#> 117 184 16.1 154.1 32 107 10 169 167.2 99 145 23.1 190
#> 17.46 17.77 8.71 12.63 20.90 11.18 10.53 22.41 15.55 21.19 10.07 16.92 20.81
#> 139 180 136 78 150.1 24 145.1 117.1 108.1 23.2 188.1 167.3 140
#> 21.49 14.82 21.83 23.88 20.33 23.89 10.07 17.46 18.29 16.92 16.16 15.55 12.68
#> 136.1 16.2 5 164.1 99.1 39.1 184.1 99.2 52.1 140.1 197 29.1 32.1
#> 21.83 8.71 16.43 23.60 21.19 15.59 17.77 21.19 10.42 12.68 21.60 15.45 20.90
#> 92 188.2 140.2 110 51.1 111 139.1 85 90 154.2 140.3 79 61
#> 22.92 16.16 12.68 17.56 18.23 17.45 21.49 16.44 20.94 12.63 12.68 16.23 10.12
#> 76.1 170 51.2 171 129 88 56.1 15 130 177 178 72 198
#> 19.22 19.54 18.23 16.57 23.41 18.37 12.21 22.68 16.47 12.53 24.00 24.00 24.00
#> 82 144 120 12 176 109 144.1 19 7 147 7.1 185 7.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 9 83 104 147.1 104.1 65 54 3 104.2 9.1 120.1 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 54.1 9.2 12.1 138 116 94 173 116.1 54.2 120.2 152 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 119 19.1 119.1 191 193 3.1 98 119.2 174 138.1 71 19.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 53 126 3.2 94.1 135 173.1 143 71.1 74 9.3 28 120.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.2 34 146 120.4 200 132 119.3 137 173.2 161 182 193.1 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 104.3 34.1 46 44
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[79]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006819755 0.248918320 -0.001183171
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.98012939 0.01451753 0.41421745
#> grade_iii, Cure model
#> 1.48008548
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 107 11.18 1 54 1 0
#> 43 12.10 1 61 0 1
#> 57 14.46 1 45 0 1
#> 56 12.21 1 60 0 0
#> 6 15.64 1 39 0 0
#> 153 21.33 1 55 1 0
#> 23 16.92 1 61 0 0
#> 155 13.08 1 26 0 0
#> 187 9.92 1 39 1 0
#> 49 12.19 1 48 1 0
#> 49.1 12.19 1 48 1 0
#> 180 14.82 1 37 0 0
#> 192 16.44 1 31 1 0
#> 139 21.49 1 63 1 0
#> 136 21.83 1 43 0 1
#> 114 13.68 1 NA 0 0
#> 96 14.54 1 33 0 1
#> 86 23.81 1 58 0 1
#> 187.1 9.92 1 39 1 0
#> 106 16.67 1 49 1 0
#> 58 19.34 1 39 0 0
#> 70 7.38 1 30 1 0
#> 114.1 13.68 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 40 18.00 1 28 1 0
#> 66 22.13 1 53 0 0
#> 42 12.43 1 49 0 1
#> 154 12.63 1 20 1 0
#> 125 15.65 1 67 1 0
#> 42.1 12.43 1 49 0 1
#> 36 21.19 1 48 0 1
#> 127 3.53 1 62 0 1
#> 45 17.42 1 54 0 1
#> 167 15.55 1 56 1 0
#> 58.1 19.34 1 39 0 0
#> 108 18.29 1 39 0 1
#> 58.2 19.34 1 39 0 0
#> 139.1 21.49 1 63 1 0
#> 171 16.57 1 41 0 1
#> 13 14.34 1 54 0 1
#> 166 19.98 1 48 0 0
#> 197 21.60 1 69 1 0
#> 78 23.88 1 43 0 0
#> 18 15.21 1 49 1 0
#> 37 12.52 1 57 1 0
#> 184 17.77 1 38 0 0
#> 194 22.40 1 38 0 1
#> 158 20.14 1 74 1 0
#> 70.1 7.38 1 30 1 0
#> 106.1 16.67 1 49 1 0
#> 92 22.92 1 47 0 1
#> 63 22.77 1 31 1 0
#> 100 16.07 1 60 0 0
#> 77 7.27 1 67 0 1
#> 93 10.33 1 52 0 1
#> 85 16.44 1 36 0 0
#> 25 6.32 1 34 1 0
#> 56.1 12.21 1 60 0 0
#> 140 12.68 1 59 1 0
#> 136.1 21.83 1 43 0 1
#> 106.2 16.67 1 49 1 0
#> 136.2 21.83 1 43 0 1
#> 130 16.47 1 53 0 1
#> 30 17.43 1 78 0 0
#> 37.1 12.52 1 57 1 0
#> 187.2 9.92 1 39 1 0
#> 96.1 14.54 1 33 0 1
#> 157 15.10 1 47 0 0
#> 155.1 13.08 1 26 0 0
#> 158.1 20.14 1 74 1 0
#> 32 20.90 1 37 1 0
#> 6.1 15.64 1 39 0 0
#> 91 5.33 1 61 0 1
#> 36.1 21.19 1 48 0 1
#> 181 16.46 1 45 0 1
#> 50 10.02 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 128 20.35 1 35 0 1
#> 59 10.16 1 NA 1 0
#> 40.1 18.00 1 28 1 0
#> 91.1 5.33 1 61 0 1
#> 70.2 7.38 1 30 1 0
#> 39 15.59 1 37 0 1
#> 189 10.51 1 NA 1 0
#> 130.1 16.47 1 53 0 1
#> 13.1 14.34 1 54 0 1
#> 157.1 15.10 1 47 0 0
#> 56.2 12.21 1 60 0 0
#> 37.2 12.52 1 57 1 0
#> 133 14.65 1 57 0 0
#> 90.1 20.94 1 50 0 1
#> 179 18.63 1 42 0 0
#> 66.1 22.13 1 53 0 0
#> 169 22.41 1 46 0 0
#> 175 21.91 1 43 0 0
#> 10 10.53 1 34 0 0
#> 139.2 21.49 1 63 1 0
#> 55 19.34 1 69 0 1
#> 16 8.71 1 71 0 1
#> 155.2 13.08 1 26 0 0
#> 37.3 12.52 1 57 1 0
#> 129 23.41 1 53 1 0
#> 197.1 21.60 1 69 1 0
#> 86.1 23.81 1 58 0 1
#> 192.1 16.44 1 31 1 0
#> 130.2 16.47 1 53 0 1
#> 89 11.44 1 NA 0 0
#> 133.1 14.65 1 57 0 0
#> 133.2 14.65 1 57 0 0
#> 189.1 10.51 1 NA 1 0
#> 93.1 10.33 1 52 0 1
#> 188 16.16 1 46 0 1
#> 34 24.00 0 36 0 0
#> 53 24.00 0 32 0 1
#> 141 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 160 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 67 24.00 0 25 0 0
#> 131 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 161 24.00 0 45 0 0
#> 112 24.00 0 61 0 0
#> 9 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 64 24.00 0 43 0 0
#> 126 24.00 0 48 0 0
#> 132 24.00 0 55 0 0
#> 9.1 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 143 24.00 0 51 0 0
#> 33 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 11 24.00 0 42 0 1
#> 137.1 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 161.1 24.00 0 45 0 0
#> 172 24.00 0 41 0 0
#> 73 24.00 0 NA 0 1
#> 64.1 24.00 0 43 0 0
#> 122 24.00 0 66 0 0
#> 9.2 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 109 24.00 0 48 0 0
#> 185.1 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 120 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 2 24.00 0 9 0 0
#> 73.1 24.00 0 NA 0 1
#> 126.1 24.00 0 48 0 0
#> 7 24.00 0 37 1 0
#> 83 24.00 0 6 0 0
#> 118 24.00 0 44 1 0
#> 151.1 24.00 0 42 0 0
#> 143.1 24.00 0 51 0 0
#> 147.1 24.00 0 76 1 0
#> 165 24.00 0 47 0 0
#> 38 24.00 0 31 1 0
#> 126.2 24.00 0 48 0 0
#> 1.1 24.00 0 23 1 0
#> 162.1 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 137.2 24.00 0 45 1 0
#> 104 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 162.2 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 120.1 24.00 0 68 0 1
#> 131.1 24.00 0 66 0 0
#> 198 24.00 0 66 0 1
#> 132.1 24.00 0 55 0 0
#> 193.1 24.00 0 45 0 1
#> 54 24.00 0 53 1 0
#> 143.2 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 80 24.00 0 41 0 0
#> 121 24.00 0 57 1 0
#> 2.1 24.00 0 9 0 0
#> 103 24.00 0 56 1 0
#> 7.1 24.00 0 37 1 0
#> 152 24.00 0 36 0 1
#> 186 24.00 0 45 1 0
#> 151.2 24.00 0 42 0 0
#> 102 24.00 0 49 0 0
#> 132.2 24.00 0 55 0 0
#> 20.1 24.00 0 46 1 0
#> 72 24.00 0 40 0 1
#> 102.1 24.00 0 49 0 0
#> 146.1 24.00 0 63 1 0
#> 165.1 24.00 0 47 0 0
#> 176 24.00 0 43 0 1
#> 98 24.00 0 34 1 0
#> 28 24.00 0 67 1 0
#> 87 24.00 0 27 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.980 NA NA NA
#> 2 age, Cure model 0.0145 NA NA NA
#> 3 grade_ii, Cure model 0.414 NA NA NA
#> 4 grade_iii, Cure model 1.48 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00682 NA NA NA
#> 2 grade_ii, Survival model 0.249 NA NA NA
#> 3 grade_iii, Survival model -0.00118 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.98013 0.01452 0.41422 1.48009
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 246.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.98012939 0.01451753 0.41421745 1.48008548
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006819755 0.248918320 -0.001183171
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.801910225 0.790399678 0.580390557 0.733875256 0.444635725 0.118402773
#> [7] 0.298944466 0.613049927 0.859846668 0.767658354 0.767658354 0.516817647
#> [13] 0.385035094 0.096584616 0.061832216 0.558956979 0.005099368 0.859846668
#> [19] 0.308496640 0.200453788 0.906205176 0.141945783 0.252908195 0.042246155
#> [25] 0.711525124 0.656827039 0.434459295 0.711525124 0.126235551 0.988080328
#> [31] 0.289495065 0.475303009 0.200453788 0.243700522 0.200453788 0.096584616
#> [37] 0.336482514 0.591261886 0.191748976 0.082008862 0.001334210 0.485663378
#> [43] 0.667911092 0.270912085 0.035998961 0.174942663 0.906205176 0.308496640
#> [49] 0.018554793 0.024296137 0.424327441 0.940933910 0.825002479 0.385035094
#> [55] 0.952709485 0.733875256 0.645720669 0.061832216 0.308496640 0.061832216
#> [61] 0.346149958 0.280140003 0.667911092 0.859846668 0.558956979 0.496041847
#> [67] 0.613049927 0.174942663 0.158177954 0.444635725 0.964482560 0.126235551
#> [73] 0.375067310 0.848159599 0.166515278 0.252908195 0.964482560 0.906205176
#> [79] 0.464970693 0.346149958 0.591261886 0.496041847 0.733875256 0.667911092
#> [85] 0.527359842 0.141945783 0.234573725 0.042246155 0.029992628 0.054883367
#> [91] 0.813439392 0.096584616 0.200453788 0.894457205 0.613049927 0.667911092
#> [97] 0.013272005 0.082008862 0.005099368 0.385035094 0.346149958 0.527359842
#> [103] 0.527359842 0.825002479 0.414276188 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 107 43 57 56 6 153 23 155 187 49 49.1 180 192
#> 11.18 12.10 14.46 12.21 15.64 21.33 16.92 13.08 9.92 12.19 12.19 14.82 16.44
#> 139 136 96 86 187.1 106 58 70 90 40 66 42 154
#> 21.49 21.83 14.54 23.81 9.92 16.67 19.34 7.38 20.94 18.00 22.13 12.43 12.63
#> 125 42.1 36 127 45 167 58.1 108 58.2 139.1 171 13 166
#> 15.65 12.43 21.19 3.53 17.42 15.55 19.34 18.29 19.34 21.49 16.57 14.34 19.98
#> 197 78 18 37 184 194 158 70.1 106.1 92 63 100 77
#> 21.60 23.88 15.21 12.52 17.77 22.40 20.14 7.38 16.67 22.92 22.77 16.07 7.27
#> 93 85 25 56.1 140 136.1 106.2 136.2 130 30 37.1 187.2 96.1
#> 10.33 16.44 6.32 12.21 12.68 21.83 16.67 21.83 16.47 17.43 12.52 9.92 14.54
#> 157 155.1 158.1 32 6.1 91 36.1 181 145 128 40.1 91.1 70.2
#> 15.10 13.08 20.14 20.90 15.64 5.33 21.19 16.46 10.07 20.35 18.00 5.33 7.38
#> 39 130.1 13.1 157.1 56.2 37.2 133 90.1 179 66.1 169 175 10
#> 15.59 16.47 14.34 15.10 12.21 12.52 14.65 20.94 18.63 22.13 22.41 21.91 10.53
#> 139.2 55 16 155.2 37.3 129 197.1 86.1 192.1 130.2 133.1 133.2 93.1
#> 21.49 19.34 8.71 13.08 12.52 23.41 21.60 23.81 16.44 16.47 14.65 14.65 10.33
#> 188 34 53 141 147 160 47 67 131 146 185 162 151
#> 16.16 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 112 9 46 64 126 132 9.1 21 178 143 33 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 137.1 75 161.1 172 64.1 122 9.2 1 109 185.1 112.1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 2 126.1 7 83 118 151.1 143.1 147.1 165 38 126.2 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 20 137.2 104 3 3.1 162.2 119 120.1 131.1 198 132.1 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 143.2 148 80 121 2.1 103 7.1 152 186 151.2 102 132.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 72 102.1 146.1 165.1 176 98 28 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[80]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01646933 0.52669717 0.15049551
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.05293960 0.02454841 -0.46091859
#> grade_iii, Cure model
#> 0.75175192
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 49 12.19 1 48 1 0
#> 159 10.55 1 50 0 1
#> 8 18.43 1 32 0 0
#> 110 17.56 1 65 0 1
#> 90 20.94 1 50 0 1
#> 107 11.18 1 54 1 0
#> 58 19.34 1 39 0 0
#> 55 19.34 1 69 0 1
#> 188 16.16 1 46 0 1
#> 130 16.47 1 53 0 1
#> 60 13.15 1 38 1 0
#> 91 5.33 1 61 0 1
#> 61 10.12 1 36 0 1
#> 128 20.35 1 35 0 1
#> 153 21.33 1 55 1 0
#> 13 14.34 1 54 0 1
#> 76 19.22 1 54 0 1
#> 49.1 12.19 1 48 1 0
#> 92 22.92 1 47 0 1
#> 101 9.97 1 10 0 1
#> 180 14.82 1 37 0 0
#> 15 22.68 1 48 0 0
#> 29 15.45 1 68 1 0
#> 145 10.07 1 65 1 0
#> 170 19.54 1 43 0 1
#> 111 17.45 1 47 0 1
#> 23 16.92 1 61 0 0
#> 13.1 14.34 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 169 22.41 1 46 0 0
#> 190 20.81 1 42 1 0
#> 107.1 11.18 1 54 1 0
#> 77 7.27 1 67 0 1
#> 197 21.60 1 69 1 0
#> 39 15.59 1 37 0 1
#> 194 22.40 1 38 0 1
#> 158 20.14 1 74 1 0
#> 59 10.16 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 90.1 20.94 1 50 0 1
#> 85 16.44 1 36 0 0
#> 14 12.89 1 21 0 0
#> 181 16.46 1 45 0 1
#> 10 10.53 1 34 0 0
#> 24 23.89 1 38 0 0
#> 77.1 7.27 1 67 0 1
#> 139 21.49 1 63 1 0
#> 188.1 16.16 1 46 0 1
#> 13.2 14.34 1 54 0 1
#> 70 7.38 1 30 1 0
#> 110.1 17.56 1 65 0 1
#> 29.1 15.45 1 68 1 0
#> 76.1 19.22 1 54 0 1
#> 61.1 10.12 1 36 0 1
#> 15.1 22.68 1 48 0 0
#> 164 23.60 1 76 0 1
#> 181.1 16.46 1 45 0 1
#> 92.1 22.92 1 47 0 1
#> 194.1 22.40 1 38 0 1
#> 145.1 10.07 1 65 1 0
#> 91.1 5.33 1 61 0 1
#> 81 14.06 1 34 0 0
#> 105 19.75 1 60 0 0
#> 123 13.00 1 44 1 0
#> 85.1 16.44 1 36 0 0
#> 16 8.71 1 71 0 1
#> 157 15.10 1 47 0 0
#> 100 16.07 1 60 0 0
#> 117 17.46 1 26 0 1
#> 88 18.37 1 47 0 0
#> 159.1 10.55 1 50 0 1
#> 168 23.72 1 70 0 0
#> 170.1 19.54 1 43 0 1
#> 55.1 19.34 1 69 0 1
#> 123.1 13.00 1 44 1 0
#> 170.2 19.54 1 43 0 1
#> 181.2 16.46 1 45 0 1
#> 150 20.33 1 48 0 0
#> 10.1 10.53 1 34 0 0
#> 99 21.19 1 38 0 1
#> 139.1 21.49 1 63 1 0
#> 108 18.29 1 39 0 1
#> 150.1 20.33 1 48 0 0
#> 192 16.44 1 31 1 0
#> 164.1 23.60 1 76 0 1
#> 100.1 16.07 1 60 0 0
#> 155 13.08 1 26 0 0
#> 85.2 16.44 1 36 0 0
#> 154 12.63 1 20 1 0
#> 39.1 15.59 1 37 0 1
#> 158.1 20.14 1 74 1 0
#> 199 19.81 1 NA 0 1
#> 56 12.21 1 60 0 0
#> 4.1 17.64 1 NA 0 1
#> 13.3 14.34 1 54 0 1
#> 57 14.46 1 45 0 1
#> 195 11.76 1 NA 1 0
#> 100.2 16.07 1 60 0 0
#> 111.1 17.45 1 47 0 1
#> 81.1 14.06 1 34 0 0
#> 37 12.52 1 57 1 0
#> 177 12.53 1 75 0 0
#> 125 15.65 1 67 1 0
#> 18 15.21 1 49 1 0
#> 50 10.02 1 NA 1 0
#> 10.2 10.53 1 34 0 0
#> 52 10.42 1 52 0 1
#> 85.3 16.44 1 36 0 0
#> 45 17.42 1 54 0 1
#> 153.1 21.33 1 55 1 0
#> 51 18.23 1 83 0 1
#> 189 10.51 1 NA 1 0
#> 112 24.00 0 61 0 0
#> 98 24.00 0 34 1 0
#> 193 24.00 0 45 0 1
#> 95 24.00 0 68 0 1
#> 120 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 162 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 73 24.00 0 NA 0 1
#> 121 24.00 0 57 1 0
#> 152 24.00 0 36 0 1
#> 28 24.00 0 67 1 0
#> 73.1 24.00 0 NA 0 1
#> 173 24.00 0 19 0 1
#> 2 24.00 0 9 0 0
#> 198 24.00 0 66 0 1
#> 11.1 24.00 0 42 0 1
#> 141 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 98.1 24.00 0 34 1 0
#> 141.1 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 173.1 24.00 0 19 0 1
#> 44 24.00 0 56 0 0
#> 9 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 21 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 152.1 24.00 0 36 0 1
#> 137 24.00 0 45 1 0
#> 33 24.00 0 53 0 0
#> 182 24.00 0 35 0 0
#> 84 24.00 0 39 0 1
#> 102 24.00 0 49 0 0
#> 104 24.00 0 50 1 0
#> 163 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 54 24.00 0 53 1 0
#> 102.1 24.00 0 49 0 0
#> 119 24.00 0 17 0 0
#> 109 24.00 0 48 0 0
#> 185 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 73.2 24.00 0 NA 0 1
#> 17 24.00 0 38 0 1
#> 185.1 24.00 0 44 1 0
#> 185.2 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 75 24.00 0 21 1 0
#> 161 24.00 0 45 0 0
#> 28.1 24.00 0 67 1 0
#> 116 24.00 0 58 0 1
#> 122 24.00 0 66 0 0
#> 84.1 24.00 0 39 0 1
#> 119.1 24.00 0 17 0 0
#> 156 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 131 24.00 0 66 0 0
#> 138.1 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 126 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 104.1 24.00 0 50 1 0
#> 17.1 24.00 0 38 0 1
#> 156.1 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 152.2 24.00 0 36 0 1
#> 122.1 24.00 0 66 0 0
#> 38 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 62 24.00 0 71 0 0
#> 28.2 24.00 0 67 1 0
#> 115.1 24.00 0 NA 1 0
#> 137.1 24.00 0 45 1 0
#> 53 24.00 0 32 0 1
#> 176 24.00 0 43 0 1
#> 17.2 24.00 0 38 0 1
#> 185.3 24.00 0 44 1 0
#> 162.1 24.00 0 51 0 0
#> 27.1 24.00 0 63 1 0
#> 83.1 24.00 0 6 0 0
#> 53.1 24.00 0 32 0 1
#> 38.1 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 119.2 24.00 0 17 0 0
#> 152.3 24.00 0 36 0 1
#> 62.1 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.05 NA NA NA
#> 2 age, Cure model 0.0245 NA NA NA
#> 3 grade_ii, Cure model -0.461 NA NA NA
#> 4 grade_iii, Cure model 0.752 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0165 NA NA NA
#> 2 grade_ii, Survival model 0.527 NA NA NA
#> 3 grade_iii, Survival model 0.150 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05294 0.02455 -0.46092 0.75175
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258
#> Residual Deviance: 242.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05293960 0.02454841 -0.46091859 0.75175192
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01646933 0.52669717 0.15049551
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 6.712946e-01 7.297019e-01 1.224148e-01 1.511179e-01 3.503880e-02
#> [6] 7.003130e-01 9.138292e-02 9.138292e-02 3.038328e-01 2.177514e-01
#> [11] 5.449861e-01 9.662923e-01 8.210287e-01 4.698107e-02 2.463598e-02
#> [16] 4.663506e-01 1.093273e-01 6.712946e-01 2.140303e-03 8.844736e-01
#> [21] 4.411093e-01 4.636096e-03 3.926769e-01 8.525035e-01 7.526514e-02
#> [26] 1.746966e-01 2.086399e-01 4.663506e-01 8.216580e-03 4.282969e-02
#> [31] 7.003130e-01 9.332466e-01 1.552660e-02 3.694498e-01 1.057456e-02
#> [36] 6.026024e-02 1.911085e-01 3.503880e-02 2.553620e-01 6.001793e-01
#> [41] 2.270635e-01 7.596823e-01 2.720769e-05 9.332466e-01 1.847566e-02
#> [46] 3.038328e-01 4.663506e-01 9.169331e-01 1.511179e-01 3.926769e-01
#> [51] 1.093273e-01 8.210287e-01 4.636096e-03 5.719296e-04 2.270635e-01
#> [56] 2.140303e-03 1.057456e-02 8.525035e-01 9.662923e-01 5.179282e-01
#> [61] 6.998303e-02 5.725724e-01 2.553620e-01 9.006099e-01 4.287276e-01
#> [66] 3.248807e-01 1.666483e-01 1.292986e-01 7.297019e-01 1.764973e-04
#> [71] 7.526514e-02 9.138292e-02 5.725724e-01 7.526514e-02 2.270635e-01
#> [76] 5.126387e-02 7.596823e-01 3.133112e-02 1.847566e-02 1.363857e-01
#> [81] 5.126387e-02 2.553620e-01 5.719296e-04 3.248807e-01 5.587199e-01
#> [86] 2.553620e-01 6.142409e-01 3.694498e-01 6.026024e-02 6.567724e-01
#> [91] 4.663506e-01 4.536517e-01 3.248807e-01 1.746966e-01 5.179282e-01
#> [96] 6.424490e-01 6.282327e-01 3.579191e-01 4.165357e-01 7.596823e-01
#> [101] 8.053545e-01 2.553620e-01 1.997737e-01 2.463598e-02 1.436189e-01
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 49 159 8 110 90 107 58 55 188 130 60 91 61
#> 12.19 10.55 18.43 17.56 20.94 11.18 19.34 19.34 16.16 16.47 13.15 5.33 10.12
#> 128 153 13 76 49.1 92 101 180 15 29 145 170 111
#> 20.35 21.33 14.34 19.22 12.19 22.92 9.97 14.82 22.68 15.45 10.07 19.54 17.45
#> 23 13.1 169 190 107.1 77 197 39 194 158 30 90.1 85
#> 16.92 14.34 22.41 20.81 11.18 7.27 21.60 15.59 22.40 20.14 17.43 20.94 16.44
#> 14 181 10 24 77.1 139 188.1 13.2 70 110.1 29.1 76.1 61.1
#> 12.89 16.46 10.53 23.89 7.27 21.49 16.16 14.34 7.38 17.56 15.45 19.22 10.12
#> 15.1 164 181.1 92.1 194.1 145.1 91.1 81 105 123 85.1 16 157
#> 22.68 23.60 16.46 22.92 22.40 10.07 5.33 14.06 19.75 13.00 16.44 8.71 15.10
#> 100 117 88 159.1 168 170.1 55.1 123.1 170.2 181.2 150 10.1 99
#> 16.07 17.46 18.37 10.55 23.72 19.54 19.34 13.00 19.54 16.46 20.33 10.53 21.19
#> 139.1 108 150.1 192 164.1 100.1 155 85.2 154 39.1 158.1 56 13.3
#> 21.49 18.29 20.33 16.44 23.60 16.07 13.08 16.44 12.63 15.59 20.14 12.21 14.34
#> 57 100.2 111.1 81.1 37 177 125 18 10.2 52 85.3 45 153.1
#> 14.46 16.07 17.45 14.06 12.52 12.53 15.65 15.21 10.53 10.42 16.44 17.42 21.33
#> 51 112 98 193 95 120 83 162 11 121 152 28 173
#> 18.23 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 198 11.1 141 147 98.1 141.1 27 173.1 44 9 151 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 137 33 182 84 102 104 163 165 54 102.1 119 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 138 35 17 185.1 185.2 146 75 161 28.1 116 122 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 156 178 131 138.1 12 126 20 104.1 17.1 156.1 7 152.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.1 38 75.1 62 28.2 137.1 53 176 17.2 185.3 162.1 27.1 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 38.1 172 119.2 152.3 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[81]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01870391 0.29832999 0.12015641
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.298857322 0.007884021 -0.023132468
#> grade_iii, Cure model
#> 0.236294477
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 91 5.33 1 61 0 1
#> 8 18.43 1 32 0 0
#> 111 17.45 1 47 0 1
#> 6 15.64 1 39 0 0
#> 139 21.49 1 63 1 0
#> 159 10.55 1 50 0 1
#> 43 12.10 1 61 0 1
#> 181 16.46 1 45 0 1
#> 124 9.73 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 145 10.07 1 65 1 0
#> 10 10.53 1 34 0 0
#> 145.1 10.07 1 65 1 0
#> 133 14.65 1 57 0 0
#> 99 21.19 1 38 0 1
#> 194 22.40 1 38 0 1
#> 159.1 10.55 1 50 0 1
#> 154 12.63 1 20 1 0
#> 89 11.44 1 NA 0 0
#> 16 8.71 1 71 0 1
#> 85 16.44 1 36 0 0
#> 15 22.68 1 48 0 0
#> 69 23.23 1 25 0 1
#> 43.1 12.10 1 61 0 1
#> 171 16.57 1 41 0 1
#> 189 10.51 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 29 15.45 1 68 1 0
#> 145.2 10.07 1 65 1 0
#> 92 22.92 1 47 0 1
#> 43.2 12.10 1 61 0 1
#> 110 17.56 1 65 0 1
#> 124.1 9.73 1 NA 1 0
#> 89.1 11.44 1 NA 0 0
#> 155 13.08 1 26 0 0
#> 183 9.24 1 67 1 0
#> 134 17.81 1 47 1 0
#> 69.1 23.23 1 25 0 1
#> 32 20.90 1 37 1 0
#> 124.2 9.73 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 26 15.77 1 49 0 1
#> 110.1 17.56 1 65 0 1
#> 187 9.92 1 39 1 0
#> 23 16.92 1 61 0 0
#> 189.1 10.51 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 155.1 13.08 1 26 0 0
#> 8.1 18.43 1 32 0 0
#> 77 7.27 1 67 0 1
#> 81 14.06 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 189.2 10.51 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 10.1 10.53 1 34 0 0
#> 133.1 14.65 1 57 0 0
#> 199.1 19.81 1 NA 0 1
#> 184 17.77 1 38 0 0
#> 133.2 14.65 1 57 0 0
#> 123 13.00 1 44 1 0
#> 153 21.33 1 55 1 0
#> 134.1 17.81 1 47 1 0
#> 45 17.42 1 54 0 1
#> 195 11.76 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 158 20.14 1 74 1 0
#> 37.1 12.52 1 57 1 0
#> 15.1 22.68 1 48 0 0
#> 29.1 15.45 1 68 1 0
#> 167 15.55 1 56 1 0
#> 113 22.86 1 34 0 0
#> 91.1 5.33 1 61 0 1
#> 41 18.02 1 40 1 0
#> 192 16.44 1 31 1 0
#> 8.2 18.43 1 32 0 0
#> 23.1 16.92 1 61 0 0
#> 18 15.21 1 49 1 0
#> 150 20.33 1 48 0 0
#> 57 14.46 1 45 0 1
#> 114 13.68 1 NA 0 0
#> 13 14.34 1 54 0 1
#> 85.1 16.44 1 36 0 0
#> 177 12.53 1 75 0 0
#> 110.2 17.56 1 65 0 1
#> 77.1 7.27 1 67 0 1
#> 61 10.12 1 36 0 1
#> 157 15.10 1 47 0 0
#> 167.1 15.55 1 56 1 0
#> 133.3 14.65 1 57 0 0
#> 100 16.07 1 60 0 0
#> 58 19.34 1 39 0 0
#> 79 16.23 1 54 1 0
#> 50 10.02 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 145.3 10.07 1 65 1 0
#> 6.1 15.64 1 39 0 0
#> 5 16.43 1 51 0 1
#> 10.2 10.53 1 34 0 0
#> 150.1 20.33 1 48 0 0
#> 110.3 17.56 1 65 0 1
#> 154.1 12.63 1 20 1 0
#> 179 18.63 1 42 0 0
#> 134.2 17.81 1 47 1 0
#> 117 17.46 1 26 0 1
#> 154.2 12.63 1 20 1 0
#> 70 7.38 1 30 1 0
#> 41.1 18.02 1 40 1 0
#> 39 15.59 1 37 0 1
#> 57.1 14.46 1 45 0 1
#> 124.3 9.73 1 NA 1 0
#> 125.1 15.65 1 67 1 0
#> 195.1 11.76 1 NA 1 0
#> 104 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#> 62 24.00 0 71 0 0
#> 131 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 131.1 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 27 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 64 24.00 0 43 0 0
#> 20 24.00 0 46 1 0
#> 173 24.00 0 19 0 1
#> 151 24.00 0 42 0 0
#> 28 24.00 0 67 1 0
#> 47 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 115 24.00 0 NA 1 0
#> 84 24.00 0 39 0 1
#> 160 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 172 24.00 0 41 0 0
#> 151.1 24.00 0 42 0 0
#> 94 24.00 0 51 0 1
#> 163 24.00 0 66 0 0
#> 173.1 24.00 0 19 0 1
#> 178 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 174 24.00 0 49 1 0
#> 173.2 24.00 0 19 0 1
#> 83 24.00 0 6 0 0
#> 131.2 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 80 24.00 0 41 0 0
#> 103 24.00 0 56 1 0
#> 11 24.00 0 42 0 1
#> 191 24.00 0 60 0 1
#> 115.1 24.00 0 NA 1 0
#> 118.1 24.00 0 44 1 0
#> 174.1 24.00 0 49 1 0
#> 20.1 24.00 0 46 1 0
#> 165 24.00 0 47 0 0
#> 146 24.00 0 63 1 0
#> 121.1 24.00 0 57 1 0
#> 80.1 24.00 0 41 0 0
#> 161 24.00 0 45 0 0
#> 35 24.00 0 51 0 0
#> 163.1 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 31 24.00 0 36 0 1
#> 137 24.00 0 45 1 0
#> 116.1 24.00 0 58 0 1
#> 98 24.00 0 34 1 0
#> 152 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 1 24.00 0 23 1 0
#> 87 24.00 0 27 0 0
#> 94.1 24.00 0 51 0 1
#> 176 24.00 0 43 0 1
#> 142 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 161.1 24.00 0 45 0 0
#> 112 24.00 0 61 0 0
#> 17 24.00 0 38 0 1
#> 102.1 24.00 0 49 0 0
#> 12 24.00 0 63 0 0
#> 72.1 24.00 0 40 0 1
#> 182 24.00 0 35 0 0
#> 87.1 24.00 0 27 0 0
#> 109.1 24.00 0 48 0 0
#> 73.1 24.00 0 NA 0 1
#> 94.2 24.00 0 51 0 1
#> 65.1 24.00 0 57 1 0
#> 120.1 24.00 0 68 0 1
#> 148 24.00 0 61 1 0
#> 144 24.00 0 28 0 1
#> 20.2 24.00 0 46 1 0
#> 141.1 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 74 24.00 0 43 0 1
#> 143 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.299 NA NA NA
#> 2 age, Cure model 0.00788 NA NA NA
#> 3 grade_ii, Cure model -0.0231 NA NA NA
#> 4 grade_iii, Cure model 0.236 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0187 NA NA NA
#> 2 grade_ii, Survival model 0.298 NA NA NA
#> 3 grade_iii, Survival model 0.120 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.298857 0.007884 -0.023132 0.236294
#>
#> Degrees of Freedom: 180 Total (i.e. Null); 177 Residual
#> Null Deviance: 250
#> Residual Deviance: 248.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.298857322 0.007884021 -0.023132468 0.236294477
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01870391 0.29832999 0.12015641
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9931348 0.5781773 0.7049838 0.7987313 0.4463973 0.9331977 0.9210750
#> [8] 0.7386146 0.6087610 0.9568930 0.9411676 0.9568930 0.8451880 0.4789386
#> [15] 0.4060440 0.9331977 0.8953079 0.9789803 0.7450564 0.3627868 0.1925740
#> [22] 0.9210750 0.7320808 0.9126958 0.8254638 0.9568930 0.2713049 0.9210750
#> [29] 0.6694118 0.8819133 0.9753444 0.6365477 0.1925740 0.5066985 0.4268089
#> [36] 0.7818161 0.6694118 0.9716574 0.7189042 0.7876721 0.8819133 0.5781773
#> [43] 0.9861475 0.8773966 0.4789386 0.9411676 0.8451880 0.6611978 0.8451880
#> [50] 0.8908663 0.4634571 0.6365477 0.7120153 0.1231084 0.5448492 0.9126958
#> [57] 0.3627868 0.8254638 0.8150497 0.3049618 0.9931348 0.6184195 0.7450564
#> [64] 0.5781773 0.7189042 0.8354006 0.5201421 0.8637082 0.8728591 0.7450564
#> [71] 0.9083808 0.6694118 0.9861475 0.9529642 0.8403143 0.8150497 0.8451880
#> [78] 0.7758792 0.5562056 0.7698466 0.3356176 0.9568930 0.7987313 0.7636837
#> [85] 0.9411676 0.5201421 0.6694118 0.8953079 0.5673184 0.6365477 0.6978298
#> [92] 0.8953079 0.9825728 0.6184195 0.8096285 0.8637082 0.7876721 0.0000000
#> [99] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 91 8 111 6 139 159 43 181 51 145 10 145.1 133
#> 5.33 18.43 17.45 15.64 21.49 10.55 12.10 16.46 18.23 10.07 10.53 10.07 14.65
#> 99 194 159.1 154 16 85 15 69 43.1 171 37 29 145.2
#> 21.19 22.40 10.55 12.63 8.71 16.44 22.68 23.23 12.10 16.57 12.52 15.45 10.07
#> 92 43.2 110 155 183 134 69.1 32 175 26 110.1 187 23
#> 22.92 12.10 17.56 13.08 9.24 17.81 23.23 20.90 21.91 15.77 17.56 9.92 16.92
#> 125 155.1 8.1 77 81 36 10.1 133.1 184 133.2 123 153 134.1
#> 15.65 13.08 18.43 7.27 14.06 21.19 10.53 14.65 17.77 14.65 13.00 21.33 17.81
#> 45 78 158 37.1 15.1 29.1 167 113 91.1 41 192 8.2 23.1
#> 17.42 23.88 20.14 12.52 22.68 15.45 15.55 22.86 5.33 18.02 16.44 18.43 16.92
#> 18 150 57 13 85.1 177 110.2 77.1 61 157 167.1 133.3 100
#> 15.21 20.33 14.46 14.34 16.44 12.53 17.56 7.27 10.12 15.10 15.55 14.65 16.07
#> 58 79 63 145.3 6.1 5 10.2 150.1 110.3 154.1 179 134.2 117
#> 19.34 16.23 22.77 10.07 15.64 16.43 10.53 20.33 17.56 12.63 18.63 17.81 17.46
#> 154.2 70 41.1 39 57.1 125.1 104 95 62 131 118 131.1 48
#> 12.63 7.38 18.02 15.59 14.46 15.65 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 120 27 116 64 20 173 151 28 47 141 71 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 160 65 172 151.1 94 163 173.1 178 121 174 173.2 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.2 102 80 103 11 191 118.1 174.1 20.1 165 146 121.1 80.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 35 163.1 9 109 147 31 137 116.1 98 152 132 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 94.1 176 142 38 186 161.1 112 17 102.1 12 72.1 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 109.1 94.2 65.1 120.1 148 144 20.2 141.1 193 74 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[82]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01021239 0.76387035 0.53878395
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.34963160 0.02538893 -0.01566328
#> grade_iii, Cure model
#> 0.99992758
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 158 20.14 1 74 1 0
#> 78 23.88 1 43 0 0
#> 10 10.53 1 34 0 0
#> 66 22.13 1 53 0 0
#> 189 10.51 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 150 20.33 1 48 0 0
#> 51 18.23 1 83 0 1
#> 197 21.60 1 69 1 0
#> 16 8.71 1 71 0 1
#> 13 14.34 1 54 0 1
#> 30 17.43 1 78 0 0
#> 136 21.83 1 43 0 1
#> 16.1 8.71 1 71 0 1
#> 117 17.46 1 26 0 1
#> 136.1 21.83 1 43 0 1
#> 181 16.46 1 45 0 1
#> 91 5.33 1 61 0 1
#> 26 15.77 1 49 0 1
#> 166 19.98 1 48 0 0
#> 86 23.81 1 58 0 1
#> 181.1 16.46 1 45 0 1
#> 170 19.54 1 43 0 1
#> 88 18.37 1 47 0 0
#> 168 23.72 1 70 0 0
#> 170.1 19.54 1 43 0 1
#> 89 11.44 1 NA 0 0
#> 88.1 18.37 1 47 0 0
#> 78.1 23.88 1 43 0 0
#> 128 20.35 1 35 0 1
#> 100 16.07 1 60 0 0
#> 90 20.94 1 50 0 1
#> 180 14.82 1 37 0 0
#> 32 20.90 1 37 1 0
#> 154 12.63 1 20 1 0
#> 194 22.40 1 38 0 1
#> 113 22.86 1 34 0 0
#> 108 18.29 1 39 0 1
#> 8 18.43 1 32 0 0
#> 6 15.64 1 39 0 0
#> 129 23.41 1 53 1 0
#> 111 17.45 1 47 0 1
#> 136.2 21.83 1 43 0 1
#> 177 12.53 1 75 0 0
#> 69 23.23 1 25 0 1
#> 187 9.92 1 39 1 0
#> 170.2 19.54 1 43 0 1
#> 150.1 20.33 1 48 0 0
#> 159 10.55 1 50 0 1
#> 88.2 18.37 1 47 0 0
#> 51.1 18.23 1 83 0 1
#> 36 21.19 1 48 0 1
#> 100.1 16.07 1 60 0 0
#> 60 13.15 1 38 1 0
#> 40 18.00 1 28 1 0
#> 139 21.49 1 63 1 0
#> 140 12.68 1 59 1 0
#> 110 17.56 1 65 0 1
#> 5 16.43 1 51 0 1
#> 16.2 8.71 1 71 0 1
#> 189.1 10.51 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 145 10.07 1 65 1 0
#> 77 7.27 1 67 0 1
#> 183 9.24 1 67 1 0
#> 110.1 17.56 1 65 0 1
#> 78.2 23.88 1 43 0 0
#> 4 17.64 1 NA 0 1
#> 56 12.21 1 60 0 0
#> 170.3 19.54 1 43 0 1
#> 77.1 7.27 1 67 0 1
#> 136.3 21.83 1 43 0 1
#> 10.1 10.53 1 34 0 0
#> 101 9.97 1 10 0 1
#> 108.1 18.29 1 39 0 1
#> 113.1 22.86 1 34 0 0
#> 5.1 16.43 1 51 0 1
#> 90.1 20.94 1 50 0 1
#> 170.4 19.54 1 43 0 1
#> 145.1 10.07 1 65 1 0
#> 59 10.16 1 NA 1 0
#> 150.2 20.33 1 48 0 0
#> 168.1 23.72 1 70 0 0
#> 166.1 19.98 1 48 0 0
#> 30.1 17.43 1 78 0 0
#> 55 19.34 1 69 0 1
#> 194.1 22.40 1 38 0 1
#> 184 17.77 1 38 0 0
#> 150.3 20.33 1 48 0 0
#> 91.1 5.33 1 61 0 1
#> 133 14.65 1 57 0 0
#> 78.3 23.88 1 43 0 0
#> 92 22.92 1 47 0 1
#> 183.1 9.24 1 67 1 0
#> 77.2 7.27 1 67 0 1
#> 124 9.73 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 189.2 10.51 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 76.1 19.22 1 54 0 1
#> 140.1 12.68 1 59 1 0
#> 57 14.46 1 45 0 1
#> 114 13.68 1 NA 0 0
#> 85 16.44 1 36 0 0
#> 140.2 12.68 1 59 1 0
#> 105 19.75 1 60 0 0
#> 134 17.81 1 47 1 0
#> 168.2 23.72 1 70 0 0
#> 40.1 18.00 1 28 1 0
#> 158.1 20.14 1 74 1 0
#> 113.2 22.86 1 34 0 0
#> 125 15.65 1 67 1 0
#> 62 24.00 0 71 0 0
#> 162 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 120 24.00 0 68 0 1
#> 196 24.00 0 19 0 0
#> 103 24.00 0 56 1 0
#> 44 24.00 0 56 0 0
#> 109 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 102 24.00 0 49 0 0
#> 2 24.00 0 9 0 0
#> 119.1 24.00 0 17 0 0
#> 12 24.00 0 63 0 0
#> 54 24.00 0 53 1 0
#> 185 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 173 24.00 0 19 0 1
#> 84 24.00 0 39 0 1
#> 80 24.00 0 41 0 0
#> 12.1 24.00 0 63 0 0
#> 104 24.00 0 50 1 0
#> 102.1 24.00 0 49 0 0
#> 198 24.00 0 66 0 1
#> 151 24.00 0 42 0 0
#> 152 24.00 0 36 0 1
#> 138 24.00 0 44 1 0
#> 84.1 24.00 0 39 0 1
#> 3 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 185.1 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 46 24.00 0 71 0 0
#> 102.2 24.00 0 49 0 0
#> 83 24.00 0 6 0 0
#> 165 24.00 0 47 0 0
#> 74 24.00 0 43 0 1
#> 82 24.00 0 34 0 0
#> 34 24.00 0 36 0 0
#> 176 24.00 0 43 0 1
#> 75 24.00 0 21 1 0
#> 67.1 24.00 0 25 0 0
#> 138.1 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 17 24.00 0 38 0 1
#> 80.1 24.00 0 41 0 0
#> 119.2 24.00 0 17 0 0
#> 19 24.00 0 57 0 1
#> 27 24.00 0 63 1 0
#> 172 24.00 0 41 0 0
#> 151.1 24.00 0 42 0 0
#> 185.2 24.00 0 44 1 0
#> 102.3 24.00 0 49 0 0
#> 73 24.00 0 NA 0 1
#> 28 24.00 0 67 1 0
#> 47 24.00 0 38 0 1
#> 94.1 24.00 0 51 0 1
#> 94.2 24.00 0 51 0 1
#> 44.1 24.00 0 56 0 0
#> 132 24.00 0 55 0 0
#> 80.2 24.00 0 41 0 0
#> 196.1 24.00 0 19 0 0
#> 80.3 24.00 0 41 0 0
#> 104.1 24.00 0 50 1 0
#> 162.1 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 178 24.00 0 52 1 0
#> 102.4 24.00 0 49 0 0
#> 54.1 24.00 0 53 1 0
#> 112 24.00 0 61 0 0
#> 11 24.00 0 42 0 1
#> 122 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 122.1 24.00 0 66 0 0
#> 126 24.00 0 48 0 0
#> 27.1 24.00 0 63 1 0
#> 84.2 24.00 0 39 0 1
#> 64.1 24.00 0 43 0 0
#> 115 24.00 0 NA 1 0
#> 198.1 24.00 0 66 0 1
#> 135 24.00 0 58 1 0
#> 141.1 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 152.1 24.00 0 36 0 1
#> 161.2 24.00 0 45 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.35 NA NA NA
#> 2 age, Cure model 0.0254 NA NA NA
#> 3 grade_ii, Cure model -0.0157 NA NA NA
#> 4 grade_iii, Cure model 1.00 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0102 NA NA NA
#> 2 grade_ii, Survival model 0.764 NA NA NA
#> 3 grade_iii, Survival model 0.539 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.34963 0.02539 -0.01566 0.99993
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 245.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.34963160 0.02538893 -0.01566328 0.99992758
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01021239 0.76387035 0.53878395
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6346411 0.1342702 0.9379088 0.4699347 0.8989642 0.6022591 0.7612213
#> [8] 0.5276745 0.9703234 0.8897841 0.8163384 0.4835066 0.9703234 0.8057781
#> [15] 0.4835066 0.8266432 0.9927361 0.8613650 0.6496583 0.2558137 0.8266432
#> [22] 0.6718315 0.7305475 0.2848389 0.6718315 0.7305475 0.1342702 0.5936979
#> [29] 0.8516195 0.5580465 0.8756892 0.5761350 0.9209127 0.4426249 0.3981824
#> [36] 0.7491079 0.7242075 0.8709516 0.3459421 0.8110887 0.4835066 0.9251959
#> [43] 0.3645124 0.9584773 0.6718315 0.6022591 0.9337003 0.7305475 0.7612213
#> [50] 0.5483390 0.8516195 0.8943996 0.7727827 0.5383123 0.9080256 0.7951054
#> [57] 0.8417788 0.9703234 0.7115402 0.9462758 0.9816831 0.9625025 0.7951054
#> [64] 0.1342702 0.9294563 0.6718315 0.9816831 0.4835066 0.9379088 0.9544148
#> [71] 0.7491079 0.3981824 0.8417788 0.5580465 0.6718315 0.9462758 0.6022591
#> [78] 0.2848389 0.6496583 0.8163384 0.7049452 0.4426249 0.7895777 0.6022591
#> [85] 0.9927361 0.8804149 0.1342702 0.3820028 0.9625025 0.9816831 0.5849538
#> [92] 0.9035217 0.7115402 0.9080256 0.8851207 0.8367324 0.9080256 0.6644592
#> [99] 0.7840315 0.2848389 0.7727827 0.6346411 0.3981824 0.8662015 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000
#>
#> $Time
#> 158 78 10 66 155 150 51 197 16 13 30 136 16.1
#> 20.14 23.88 10.53 22.13 13.08 20.33 18.23 21.60 8.71 14.34 17.43 21.83 8.71
#> 117 136.1 181 91 26 166 86 181.1 170 88 168 170.1 88.1
#> 17.46 21.83 16.46 5.33 15.77 19.98 23.81 16.46 19.54 18.37 23.72 19.54 18.37
#> 78.1 128 100 90 180 32 154 194 113 108 8 6 129
#> 23.88 20.35 16.07 20.94 14.82 20.90 12.63 22.40 22.86 18.29 18.43 15.64 23.41
#> 111 136.2 177 69 187 170.2 150.1 159 88.2 51.1 36 100.1 60
#> 17.45 21.83 12.53 23.23 9.92 19.54 20.33 10.55 18.37 18.23 21.19 16.07 13.15
#> 40 139 140 110 5 16.2 76 145 77 183 110.1 78.2 56
#> 18.00 21.49 12.68 17.56 16.43 8.71 19.22 10.07 7.27 9.24 17.56 23.88 12.21
#> 170.3 77.1 136.3 10.1 101 108.1 113.1 5.1 90.1 170.4 145.1 150.2 168.1
#> 19.54 7.27 21.83 10.53 9.97 18.29 22.86 16.43 20.94 19.54 10.07 20.33 23.72
#> 166.1 30.1 55 194.1 184 150.3 91.1 133 78.3 92 183.1 77.2 68
#> 19.98 17.43 19.34 22.40 17.77 20.33 5.33 14.65 23.88 22.92 9.24 7.27 20.62
#> 123 76.1 140.1 57 85 140.2 105 134 168.2 40.1 158.1 113.2 125
#> 13.00 19.22 12.68 14.46 16.44 12.68 19.75 17.81 23.72 18.00 20.14 22.86 15.65
#> 62 162 118 160 161 120 196 103 44 109 95 119 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 119.1 12 54 185 67 173 84 80 12.1 104 102.1 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 152 138 84.1 3 161.1 185.1 141 94 46 102.2 83 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 82 34 176 75 67.1 138.1 64 17 80.1 119.2 19 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 151.1 185.2 102.3 28 47 94.1 94.2 44.1 132 80.2 196.1 80.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 162.1 200 178 102.4 54.1 112 11 122 174 122.1 126 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84.2 64.1 198.1 135 141.1 48 152.1 161.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[83]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003106953 0.760719238 -0.033552731
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.513059339 0.008298478 0.336093503
#> grade_iii, Cure model
#> 0.595538350
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 26 15.77 1 49 0 1
#> 111 17.45 1 47 0 1
#> 149 8.37 1 33 1 0
#> 107 11.18 1 54 1 0
#> 157 15.10 1 47 0 0
#> 175 21.91 1 43 0 0
#> 58 19.34 1 39 0 0
#> 86 23.81 1 58 0 1
#> 39 15.59 1 37 0 1
#> 90 20.94 1 50 0 1
#> 128 20.35 1 35 0 1
#> 69 23.23 1 25 0 1
#> 79 16.23 1 54 1 0
#> 32 20.90 1 37 1 0
#> 188 16.16 1 46 0 1
#> 177 12.53 1 75 0 0
#> 16 8.71 1 71 0 1
#> 136 21.83 1 43 0 1
#> 155 13.08 1 26 0 0
#> 13 14.34 1 54 0 1
#> 101 9.97 1 10 0 1
#> 85 16.44 1 36 0 0
#> 96 14.54 1 33 0 1
#> 170 19.54 1 43 0 1
#> 171 16.57 1 41 0 1
#> 127 3.53 1 62 0 1
#> 30 17.43 1 78 0 0
#> 195 11.76 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 13.1 14.34 1 54 0 1
#> 10 10.53 1 34 0 0
#> 181 16.46 1 45 0 1
#> 25 6.32 1 34 1 0
#> 89 11.44 1 NA 0 0
#> 153 21.33 1 55 1 0
#> 140 12.68 1 59 1 0
#> 15 22.68 1 48 0 0
#> 85.1 16.44 1 36 0 0
#> 59 10.16 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 145 10.07 1 65 1 0
#> 5 16.43 1 51 0 1
#> 5.1 16.43 1 51 0 1
#> 139 21.49 1 63 1 0
#> 41 18.02 1 40 1 0
#> 10.1 10.53 1 34 0 0
#> 195.1 11.76 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 30.1 17.43 1 78 0 0
#> 107.1 11.18 1 54 1 0
#> 69.1 23.23 1 25 0 1
#> 171.1 16.57 1 41 0 1
#> 188.1 16.16 1 46 0 1
#> 99 21.19 1 38 0 1
#> 45 17.42 1 54 0 1
#> 90.1 20.94 1 50 0 1
#> 81 14.06 1 34 0 0
#> 6 15.64 1 39 0 0
#> 92 22.92 1 47 0 1
#> 149.1 8.37 1 33 1 0
#> 70 7.38 1 30 1 0
#> 60 13.15 1 38 1 0
#> 164 23.60 1 76 0 1
#> 177.1 12.53 1 75 0 0
#> 107.2 11.18 1 54 1 0
#> 179 18.63 1 42 0 0
#> 57 14.46 1 45 0 1
#> 194 22.40 1 38 0 1
#> 108 18.29 1 39 0 1
#> 55 19.34 1 69 0 1
#> 175.1 21.91 1 43 0 0
#> 89.1 11.44 1 NA 0 0
#> 37 12.52 1 57 1 0
#> 130 16.47 1 53 0 1
#> 192 16.44 1 31 1 0
#> 13.2 14.34 1 54 0 1
#> 66 22.13 1 53 0 0
#> 190 20.81 1 42 1 0
#> 167 15.55 1 56 1 0
#> 130.1 16.47 1 53 0 1
#> 69.2 23.23 1 25 0 1
#> 150 20.33 1 48 0 0
#> 183 9.24 1 67 1 0
#> 187 9.92 1 39 1 0
#> 30.2 17.43 1 78 0 0
#> 30.3 17.43 1 78 0 0
#> 117 17.46 1 26 0 1
#> 97 19.14 1 65 0 1
#> 18 15.21 1 49 1 0
#> 140.1 12.68 1 59 1 0
#> 93 10.33 1 52 0 1
#> 197 21.60 1 69 1 0
#> 61 10.12 1 36 0 1
#> 154 12.63 1 20 1 0
#> 58.1 19.34 1 39 0 0
#> 179.1 18.63 1 42 0 0
#> 189 10.51 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 181.1 16.46 1 45 0 1
#> 16.1 8.71 1 71 0 1
#> 101.1 9.97 1 10 0 1
#> 78 23.88 1 43 0 0
#> 60.1 13.15 1 38 1 0
#> 113 22.86 1 34 0 0
#> 92.1 22.92 1 47 0 1
#> 180 14.82 1 37 0 0
#> 158 20.14 1 74 1 0
#> 175.2 21.91 1 43 0 0
#> 81.1 14.06 1 34 0 0
#> 81.2 14.06 1 34 0 0
#> 90.2 20.94 1 50 0 1
#> 13.3 14.34 1 54 0 1
#> 200 24.00 0 64 0 0
#> 27 24.00 0 63 1 0
#> 21 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 53 24.00 0 32 0 1
#> 176 24.00 0 43 0 1
#> 191 24.00 0 60 0 1
#> 62 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 122 24.00 0 66 0 0
#> 62.1 24.00 0 71 0 0
#> 147 24.00 0 76 1 0
#> 74 24.00 0 43 0 1
#> 148 24.00 0 61 1 0
#> 115.1 24.00 0 NA 1 0
#> 84 24.00 0 39 0 1
#> 144 24.00 0 28 0 1
#> 126 24.00 0 48 0 0
#> 137 24.00 0 45 1 0
#> 119 24.00 0 17 0 0
#> 141 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 186 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 104 24.00 0 50 1 0
#> 71 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 80 24.00 0 41 0 0
#> 138 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 87 24.00 0 27 0 0
#> 121 24.00 0 57 1 0
#> 2 24.00 0 9 0 0
#> 144.1 24.00 0 28 0 1
#> 173 24.00 0 19 0 1
#> 121.1 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 193 24.00 0 45 0 1
#> 53.1 24.00 0 32 0 1
#> 162 24.00 0 51 0 0
#> 200.1 24.00 0 64 0 0
#> 144.2 24.00 0 28 0 1
#> 74.1 24.00 0 43 0 1
#> 126.1 24.00 0 48 0 0
#> 165 24.00 0 47 0 0
#> 27.1 24.00 0 63 1 0
#> 162.1 24.00 0 51 0 0
#> 172.1 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 74.2 24.00 0 43 0 1
#> 200.2 24.00 0 64 0 0
#> 144.3 24.00 0 28 0 1
#> 156 24.00 0 50 1 0
#> 135 24.00 0 58 1 0
#> 27.2 24.00 0 63 1 0
#> 198.1 24.00 0 66 0 1
#> 12 24.00 0 63 0 0
#> 185 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 144.4 24.00 0 28 0 1
#> 64 24.00 0 43 0 0
#> 74.3 24.00 0 43 0 1
#> 132 24.00 0 55 0 0
#> 198.2 24.00 0 66 0 1
#> 80.1 24.00 0 41 0 0
#> 87.1 24.00 0 27 0 0
#> 121.2 24.00 0 57 1 0
#> 31 24.00 0 36 0 1
#> 19 24.00 0 57 0 1
#> 174 24.00 0 49 1 0
#> 2.1 24.00 0 9 0 0
#> 53.2 24.00 0 32 0 1
#> 118 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 72 24.00 0 40 0 1
#> 132.1 24.00 0 55 0 0
#> 80.2 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 142.1 24.00 0 53 0 0
#> 185.1 24.00 0 44 1 0
#> 173.1 24.00 0 19 0 1
#> 161 24.00 0 45 0 0
#> 74.4 24.00 0 43 0 1
#> 27.3 24.00 0 63 1 0
#> 74.5 24.00 0 43 0 1
#> 102 24.00 0 49 0 0
#> 176.1 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.513 NA NA NA
#> 2 age, Cure model 0.00830 NA NA NA
#> 3 grade_ii, Cure model 0.336 NA NA NA
#> 4 grade_iii, Cure model 0.596 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00311 NA NA NA
#> 2 grade_ii, Survival model 0.761 NA NA NA
#> 3 grade_iii, Survival model -0.0336 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.513059 0.008298 0.336094 0.595538
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 259.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.513059339 0.008298478 0.336093503 0.595538350
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003106953 0.760719238 -0.033552731
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.585484728 0.382858789 0.957181923 0.833397029 0.634236053 0.119319176
#> [7] 0.288803024 0.011584718 0.605096927 0.202905367 0.251196054 0.031590544
#> [13] 0.556391716 0.232019930 0.566109410 0.796485839 0.939671741 0.150573135
#> [19] 0.758982367 0.672774097 0.904383647 0.507993420 0.653468022 0.279467980
#> [25] 0.449286629 0.991479288 0.392369471 0.824249254 0.672774097 0.859843275
#> [31] 0.488291949 0.982973374 0.183079244 0.768552181 0.086618653 0.507993420
#> [37] 0.895496845 0.536852314 0.536852314 0.172754639 0.363940703 0.859843275
#> [43] 0.439527928 0.392369471 0.833397029 0.031590544 0.449286629 0.566109410
#> [49] 0.192956435 0.429806500 0.202905367 0.710998422 0.595281608 0.056691087
#> [55] 0.957181923 0.974398805 0.739981878 0.020989983 0.796485839 0.833397029
#> [61] 0.325803936 0.663109875 0.097348749 0.344668249 0.288803024 0.119319176
#> [67] 0.815015050 0.468716285 0.507993420 0.672774097 0.108248934 0.241774825
#> [73] 0.614934270 0.468716285 0.031590544 0.260664421 0.930912288 0.922091609
#> [79] 0.392369471 0.392369471 0.373386796 0.316299623 0.624647605 0.768552181
#> [85] 0.877602449 0.161939534 0.886543537 0.787211834 0.288803024 0.325803936
#> [91] 0.354271339 0.488291949 0.939671741 0.904383647 0.003694157 0.739981878
#> [97] 0.076071005 0.056691087 0.643844238 0.270180712 0.119319176 0.710998422
#> [103] 0.710998422 0.202905367 0.672774097 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 26 111 149 107 157 175 58 86 39 90 128 69 79
#> 15.77 17.45 8.37 11.18 15.10 21.91 19.34 23.81 15.59 20.94 20.35 23.23 16.23
#> 32 188 177 16 136 155 13 101 85 96 170 171 127
#> 20.90 16.16 12.53 8.71 21.83 13.08 14.34 9.97 16.44 14.54 19.54 16.57 3.53
#> 30 49 13.1 10 181 25 153 140 15 85.1 145 5 5.1
#> 17.43 12.19 14.34 10.53 16.46 6.32 21.33 12.68 22.68 16.44 10.07 16.43 16.43
#> 139 41 10.1 23 30.1 107.1 69.1 171.1 188.1 99 45 90.1 81
#> 21.49 18.02 10.53 16.92 17.43 11.18 23.23 16.57 16.16 21.19 17.42 20.94 14.06
#> 6 92 149.1 70 60 164 177.1 107.2 179 57 194 108 55
#> 15.64 22.92 8.37 7.38 13.15 23.60 12.53 11.18 18.63 14.46 22.40 18.29 19.34
#> 175.1 37 130 192 13.2 66 190 167 130.1 69.2 150 183 187
#> 21.91 12.52 16.47 16.44 14.34 22.13 20.81 15.55 16.47 23.23 20.33 9.24 9.92
#> 30.2 30.3 117 97 18 140.1 93 197 61 154 58.1 179.1 51
#> 17.43 17.43 17.46 19.14 15.21 12.68 10.33 21.60 10.12 12.63 19.34 18.63 18.23
#> 181.1 16.1 101.1 78 60.1 113 92.1 180 158 175.2 81.1 81.2 90.2
#> 16.46 8.71 9.97 23.88 13.15 22.86 22.92 14.82 20.14 21.91 14.06 14.06 20.94
#> 13.3 200 27 21 53 176 191 62 146 122 62.1 147 74
#> 14.34 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 84 144 126 137 119 141 172 186 48 142 104 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 80 138 83 87 121 2 144.1 173 121.1 198 193 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 200.1 144.2 74.1 126.1 165 27.1 162.1 172.1 112 74.2 200.2 144.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 135 27.2 198.1 12 185 34 144.4 64 74.3 132 198.2 80.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 121.2 31 19 174 2.1 53.2 118 152 72 132.1 80.2 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 185.1 173.1 161 74.4 27.3 74.5 102 176.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[84]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006669838 0.371673971 0.205087605
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.77580776 0.01001545 0.66069703
#> grade_iii, Cure model
#> 0.92030002
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 129 23.41 1 53 1 0
#> 183 9.24 1 67 1 0
#> 125 15.65 1 67 1 0
#> 32 20.90 1 37 1 0
#> 145 10.07 1 65 1 0
#> 183.1 9.24 1 67 1 0
#> 180 14.82 1 37 0 0
#> 97 19.14 1 65 0 1
#> 125.1 15.65 1 67 1 0
#> 111 17.45 1 47 0 1
#> 25 6.32 1 34 1 0
#> 30 17.43 1 78 0 0
#> 30.1 17.43 1 78 0 0
#> 68 20.62 1 44 0 0
#> 43 12.10 1 61 0 1
#> 60 13.15 1 38 1 0
#> 192 16.44 1 31 1 0
#> 167 15.55 1 56 1 0
#> 92 22.92 1 47 0 1
#> 55 19.34 1 69 0 1
#> 114 13.68 1 NA 0 0
#> 40 18.00 1 28 1 0
#> 130 16.47 1 53 0 1
#> 133 14.65 1 57 0 0
#> 166 19.98 1 48 0 0
#> 30.2 17.43 1 78 0 0
#> 66 22.13 1 53 0 0
#> 159 10.55 1 50 0 1
#> 49 12.19 1 48 1 0
#> 66.1 22.13 1 53 0 0
#> 194 22.40 1 38 0 1
#> 184 17.77 1 38 0 0
#> 52 10.42 1 52 0 1
#> 177 12.53 1 75 0 0
#> 43.1 12.10 1 61 0 1
#> 149 8.37 1 33 1 0
#> 50 10.02 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 175 21.91 1 43 0 0
#> 105 19.75 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 14 12.89 1 21 0 0
#> 96 14.54 1 33 0 1
#> 167.1 15.55 1 56 1 0
#> 108 18.29 1 39 0 1
#> 110 17.56 1 65 0 1
#> 139 21.49 1 63 1 0
#> 23 16.92 1 61 0 0
#> 76 19.22 1 54 0 1
#> 81 14.06 1 34 0 0
#> 61 10.12 1 36 0 1
#> 192.1 16.44 1 31 1 0
#> 25.1 6.32 1 34 1 0
#> 14.1 12.89 1 21 0 0
#> 56 12.21 1 60 0 0
#> 188 16.16 1 46 0 1
#> 139.1 21.49 1 63 1 0
#> 166.1 19.98 1 48 0 0
#> 37 12.52 1 57 1 0
#> 139.2 21.49 1 63 1 0
#> 97.1 19.14 1 65 0 1
#> 187 9.92 1 39 1 0
#> 61.1 10.12 1 36 0 1
#> 78 23.88 1 43 0 0
#> 18 15.21 1 49 1 0
#> 52.1 10.42 1 52 0 1
#> 149.1 8.37 1 33 1 0
#> 24 23.89 1 38 0 0
#> 150 20.33 1 48 0 0
#> 187.1 9.92 1 39 1 0
#> 107 11.18 1 54 1 0
#> 70 7.38 1 30 1 0
#> 190 20.81 1 42 1 0
#> 108.1 18.29 1 39 0 1
#> 181 16.46 1 45 0 1
#> 111.1 17.45 1 47 0 1
#> 5 16.43 1 51 0 1
#> 51.1 18.23 1 83 0 1
#> 108.2 18.29 1 39 0 1
#> 190.1 20.81 1 42 1 0
#> 189 10.51 1 NA 1 0
#> 125.2 15.65 1 67 1 0
#> 123 13.00 1 44 1 0
#> 32.1 20.90 1 37 1 0
#> 85 16.44 1 36 0 0
#> 10 10.53 1 34 0 0
#> 110.1 17.56 1 65 0 1
#> 29 15.45 1 68 1 0
#> 32.2 20.90 1 37 1 0
#> 136 21.83 1 43 0 1
#> 134 17.81 1 47 1 0
#> 107.1 11.18 1 54 1 0
#> 61.2 10.12 1 36 0 1
#> 117 17.46 1 26 0 1
#> 79 16.23 1 54 1 0
#> 49.1 12.19 1 48 1 0
#> 42 12.43 1 49 0 1
#> 90 20.94 1 50 0 1
#> 8 18.43 1 32 0 0
#> 134.1 17.81 1 47 1 0
#> 56.1 12.21 1 60 0 0
#> 189.1 10.51 1 NA 1 0
#> 68.1 20.62 1 44 0 0
#> 139.3 21.49 1 63 1 0
#> 92.1 22.92 1 47 0 1
#> 63.1 22.77 1 31 1 0
#> 167.2 15.55 1 56 1 0
#> 177.1 12.53 1 75 0 0
#> 107.2 11.18 1 54 1 0
#> 128 20.35 1 35 0 1
#> 125.3 15.65 1 67 1 0
#> 1 24.00 0 23 1 0
#> 87 24.00 0 27 0 0
#> 173 24.00 0 19 0 1
#> 27 24.00 0 63 1 0
#> 48 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 87.1 24.00 0 27 0 0
#> 2 24.00 0 9 0 0
#> 34 24.00 0 36 0 0
#> 1.1 24.00 0 23 1 0
#> 9 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 103 24.00 0 56 1 0
#> 163 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 83 24.00 0 6 0 0
#> 163.1 24.00 0 66 0 0
#> 131 24.00 0 66 0 0
#> 31 24.00 0 36 0 1
#> 141 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 82.1 24.00 0 34 0 0
#> 27.1 24.00 0 63 1 0
#> 152 24.00 0 36 0 1
#> 102 24.00 0 49 0 0
#> 27.2 24.00 0 63 1 0
#> 143 24.00 0 51 0 0
#> 48.1 24.00 0 31 1 0
#> 102.1 24.00 0 49 0 0
#> 156 24.00 0 50 1 0
#> 115 24.00 0 NA 1 0
#> 34.1 24.00 0 36 0 0
#> 186 24.00 0 45 1 0
#> 34.2 24.00 0 36 0 0
#> 147 24.00 0 76 1 0
#> 44 24.00 0 56 0 0
#> 132 24.00 0 55 0 0
#> 198 24.00 0 66 0 1
#> 163.2 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 28 24.00 0 67 1 0
#> 2.1 24.00 0 9 0 0
#> 146.1 24.00 0 63 1 0
#> 142 24.00 0 53 0 0
#> 143.1 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 174 24.00 0 49 1 0
#> 147.1 24.00 0 76 1 0
#> 1.2 24.00 0 23 1 0
#> 142.1 24.00 0 53 0 0
#> 191 24.00 0 60 0 1
#> 47 24.00 0 38 0 1
#> 1.3 24.00 0 23 1 0
#> 185 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 186.1 24.00 0 45 1 0
#> 34.3 24.00 0 36 0 0
#> 47.1 24.00 0 38 0 1
#> 198.1 24.00 0 66 0 1
#> 146.2 24.00 0 63 1 0
#> 102.2 24.00 0 49 0 0
#> 12 24.00 0 63 0 0
#> 147.2 24.00 0 76 1 0
#> 64 24.00 0 43 0 0
#> 21 24.00 0 47 0 0
#> 12.1 24.00 0 63 0 0
#> 7 24.00 0 37 1 0
#> 82.2 24.00 0 34 0 0
#> 11 24.00 0 42 0 1
#> 200 24.00 0 64 0 0
#> 151 24.00 0 42 0 0
#> 191.1 24.00 0 60 0 1
#> 44.1 24.00 0 56 0 0
#> 71 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 48.2 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 31.1 24.00 0 36 0 1
#> 83.1 24.00 0 6 0 0
#> 142.2 24.00 0 53 0 0
#> 84 24.00 0 39 0 1
#> 27.3 24.00 0 63 1 0
#> 191.2 24.00 0 60 0 1
#> 120.1 24.00 0 68 0 1
#> 200.1 24.00 0 64 0 0
#> 72 24.00 0 40 0 1
#> 200.2 24.00 0 64 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.776 NA NA NA
#> 2 age, Cure model 0.0100 NA NA NA
#> 3 grade_ii, Cure model 0.661 NA NA NA
#> 4 grade_iii, Cure model 0.920 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00667 NA NA NA
#> 2 grade_ii, Survival model 0.372 NA NA NA
#> 3 grade_iii, Survival model 0.205 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.77581 0.01002 0.66070 0.92030
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 258.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.77580776 0.01001545 0.66069703 0.92030002
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006669838 0.371673971 0.205087605
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.11548747 0.96262971 0.72164480 0.35481042 0.94614391 0.96262971
#> [7] 0.78005022 0.49445065 0.72164480 0.61950301 0.98944607 0.63475985
#> [13] 0.63475985 0.40680723 0.87810891 0.80529471 0.67911896 0.74799376
#> [19] 0.14296163 0.47566167 0.56369443 0.66440799 0.78639549 0.44673212
#> [25] 0.63475985 0.23491378 0.90684705 0.86631405 0.23491378 0.21776624
#> [31] 0.58804483 0.91824246 0.83004559 0.87810891 0.97341677 0.18331002
#> [37] 0.26610647 0.46601673 0.54701687 0.81773010 0.79271716 0.74799376
#> [43] 0.52130928 0.59608924 0.29709810 0.65696416 0.48512528 0.79901224
#> [49] 0.92949111 0.67911896 0.98944607 0.81773010 0.85435684 0.71463663
#> [55] 0.29709810 0.44673212 0.84224362 0.29709810 0.49445065 0.95168727
#> [61] 0.92949111 0.07885213 0.77369047 0.91824246 0.97341677 0.03628697
#> [67] 0.43682028 0.95168727 0.88977155 0.98410819 0.38645025 0.52130928
#> [73] 0.67178994 0.61950301 0.70045110 0.54701687 0.52130928 0.38645025
#> [79] 0.72164480 0.81153491 0.35481042 0.67911896 0.91254928 0.59608924
#> [85] 0.76727744 0.35481042 0.28187267 0.57200320 0.88977155 0.92949111
#> [91] 0.61169556 0.70758222 0.86631405 0.84831541 0.34300521 0.51232856
#> [97] 0.57200320 0.85435684 0.40680723 0.29709810 0.14296163 0.18331002
#> [103] 0.74799376 0.83004559 0.88977155 0.42682286 0.72164480 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 129 183 125 32 145 183.1 180 97 125.1 111 25 30 30.1
#> 23.41 9.24 15.65 20.90 10.07 9.24 14.82 19.14 15.65 17.45 6.32 17.43 17.43
#> 68 43 60 192 167 92 55 40 130 133 166 30.2 66
#> 20.62 12.10 13.15 16.44 15.55 22.92 19.34 18.00 16.47 14.65 19.98 17.43 22.13
#> 159 49 66.1 194 184 52 177 43.1 149 63 175 105 51
#> 10.55 12.19 22.13 22.40 17.77 10.42 12.53 12.10 8.37 22.77 21.91 19.75 18.23
#> 14 96 167.1 108 110 139 23 76 81 61 192.1 25.1 14.1
#> 12.89 14.54 15.55 18.29 17.56 21.49 16.92 19.22 14.06 10.12 16.44 6.32 12.89
#> 56 188 139.1 166.1 37 139.2 97.1 187 61.1 78 18 52.1 149.1
#> 12.21 16.16 21.49 19.98 12.52 21.49 19.14 9.92 10.12 23.88 15.21 10.42 8.37
#> 24 150 187.1 107 70 190 108.1 181 111.1 5 51.1 108.2 190.1
#> 23.89 20.33 9.92 11.18 7.38 20.81 18.29 16.46 17.45 16.43 18.23 18.29 20.81
#> 125.2 123 32.1 85 10 110.1 29 32.2 136 134 107.1 61.2 117
#> 15.65 13.00 20.90 16.44 10.53 17.56 15.45 20.90 21.83 17.81 11.18 10.12 17.46
#> 79 49.1 42 90 8 134.1 56.1 68.1 139.3 92.1 63.1 167.2 177.1
#> 16.23 12.19 12.43 20.94 18.43 17.81 12.21 20.62 21.49 22.92 22.77 15.55 12.53
#> 107.2 128 125.3 1 87 173 27 48 138 87.1 2 34 1.1
#> 11.18 20.35 15.65 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 193 103 163 22 83 163.1 131 31 141 82 82.1 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 102 27.2 143 48.1 102.1 156 34.1 186 34.2 147 44 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 163.2 104 146 28 2.1 146.1 142 143.1 121 174 147.1 1.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 191 47 1.3 185 120 186.1 34.3 47.1 198.1 146.2 102.2 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.2 64 21 12.1 7 82.2 11 200 151 191.1 44.1 71 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.2 119 31.1 83.1 142.2 84 27.3 191.2 120.1 200.1 72 200.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[85]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003631626 0.774761293 0.443750974
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.123929467 -0.002177972 -0.048470373
#> grade_iii, Cure model
#> 0.606849003
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 24 23.89 1 38 0 0
#> 92 22.92 1 47 0 1
#> 105 19.75 1 60 0 0
#> 41 18.02 1 40 1 0
#> 101 9.97 1 10 0 1
#> 51 18.23 1 83 0 1
#> 8 18.43 1 32 0 0
#> 18 15.21 1 49 1 0
#> 159 10.55 1 50 0 1
#> 157 15.10 1 47 0 0
#> 107 11.18 1 54 1 0
#> 42 12.43 1 49 0 1
#> 76 19.22 1 54 0 1
#> 169 22.41 1 46 0 0
#> 158 20.14 1 74 1 0
#> 114 13.68 1 NA 0 0
#> 113 22.86 1 34 0 0
#> 78 23.88 1 43 0 0
#> 52 10.42 1 52 0 1
#> 85 16.44 1 36 0 0
#> 8.1 18.43 1 32 0 0
#> 42.1 12.43 1 49 0 1
#> 157.1 15.10 1 47 0 0
#> 188 16.16 1 46 0 1
#> 49 12.19 1 48 1 0
#> 136 21.83 1 43 0 1
#> 78.1 23.88 1 43 0 0
#> 85.1 16.44 1 36 0 0
#> 41.1 18.02 1 40 1 0
#> 184 17.77 1 38 0 0
#> 183 9.24 1 67 1 0
#> 14 12.89 1 21 0 0
#> 159.1 10.55 1 50 0 1
#> 117 17.46 1 26 0 1
#> 51.1 18.23 1 83 0 1
#> 36 21.19 1 48 0 1
#> 179 18.63 1 42 0 0
#> 192 16.44 1 31 1 0
#> 89 11.44 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 8.2 18.43 1 32 0 0
#> 108 18.29 1 39 0 1
#> 140 12.68 1 59 1 0
#> 159.2 10.55 1 50 0 1
#> 124 9.73 1 NA 1 0
#> 124.1 9.73 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 107.1 11.18 1 54 1 0
#> 181 16.46 1 45 0 1
#> 170 19.54 1 43 0 1
#> 60 13.15 1 38 1 0
#> 63 22.77 1 31 1 0
#> 189 10.51 1 NA 1 0
#> 60.1 13.15 1 38 1 0
#> 63.1 22.77 1 31 1 0
#> 170.1 19.54 1 43 0 1
#> 30 17.43 1 78 0 0
#> 179.1 18.63 1 42 0 0
#> 194 22.40 1 38 0 1
#> 140.1 12.68 1 59 1 0
#> 55 19.34 1 69 0 1
#> 99 21.19 1 38 0 1
#> 56 12.21 1 60 0 0
#> 76.1 19.22 1 54 0 1
#> 76.2 19.22 1 54 0 1
#> 85.2 16.44 1 36 0 0
#> 157.2 15.10 1 47 0 0
#> 24.1 23.89 1 38 0 0
#> 37 12.52 1 57 1 0
#> 55.1 19.34 1 69 0 1
#> 49.1 12.19 1 48 1 0
#> 26 15.77 1 49 0 1
#> 110 17.56 1 65 0 1
#> 199 19.81 1 NA 0 1
#> 169.1 22.41 1 46 0 0
#> 128 20.35 1 35 0 1
#> 77 7.27 1 67 0 1
#> 45 17.42 1 54 0 1
#> 127 3.53 1 62 0 1
#> 199.1 19.81 1 NA 0 1
#> 68 20.62 1 44 0 0
#> 56.1 12.21 1 60 0 0
#> 26.1 15.77 1 49 0 1
#> 24.2 23.89 1 38 0 0
#> 157.3 15.10 1 47 0 0
#> 70 7.38 1 30 1 0
#> 79 16.23 1 54 1 0
#> 96 14.54 1 33 0 1
#> 197 21.60 1 69 1 0
#> 164 23.60 1 76 0 1
#> 4 17.64 1 NA 0 1
#> 14.1 12.89 1 21 0 0
#> 60.2 13.15 1 38 1 0
#> 139 21.49 1 63 1 0
#> 107.2 11.18 1 54 1 0
#> 69 23.23 1 25 0 1
#> 113.1 22.86 1 34 0 0
#> 43 12.10 1 61 0 1
#> 36.1 21.19 1 48 0 1
#> 25 6.32 1 34 1 0
#> 183.1 9.24 1 67 1 0
#> 18.1 15.21 1 49 1 0
#> 24.3 23.89 1 38 0 0
#> 192.1 16.44 1 31 1 0
#> 153 21.33 1 55 1 0
#> 96.1 14.54 1 33 0 1
#> 10 10.53 1 34 0 0
#> 92.1 22.92 1 47 0 1
#> 145 10.07 1 65 1 0
#> 85.3 16.44 1 36 0 0
#> 100 16.07 1 60 0 0
#> 129 23.41 1 53 1 0
#> 19 24.00 0 57 0 1
#> 119 24.00 0 17 0 0
#> 82 24.00 0 34 0 0
#> 12 24.00 0 63 0 0
#> 193 24.00 0 45 0 1
#> 151 24.00 0 42 0 0
#> 103 24.00 0 56 1 0
#> 2 24.00 0 9 0 0
#> 28 24.00 0 67 1 0
#> 142 24.00 0 53 0 0
#> 28.1 24.00 0 67 1 0
#> 46 24.00 0 71 0 0
#> 112 24.00 0 61 0 0
#> 73 24.00 0 NA 0 1
#> 132 24.00 0 55 0 0
#> 20 24.00 0 46 1 0
#> 19.1 24.00 0 57 0 1
#> 27 24.00 0 63 1 0
#> 103.1 24.00 0 56 1 0
#> 87 24.00 0 27 0 0
#> 121 24.00 0 57 1 0
#> 182 24.00 0 35 0 0
#> 75 24.00 0 21 1 0
#> 119.1 24.00 0 17 0 0
#> 141 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 156 24.00 0 50 1 0
#> 193.1 24.00 0 45 0 1
#> 173 24.00 0 19 0 1
#> 35 24.00 0 51 0 0
#> 162 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 151.1 24.00 0 42 0 0
#> 80 24.00 0 41 0 0
#> 31 24.00 0 36 0 1
#> 148 24.00 0 61 1 0
#> 122 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 46.1 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 80.1 24.00 0 41 0 0
#> 147 24.00 0 76 1 0
#> 143 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 165 24.00 0 47 0 0
#> 191.1 24.00 0 60 0 1
#> 3 24.00 0 31 1 0
#> 121.1 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 94 24.00 0 51 0 1
#> 3.1 24.00 0 31 1 0
#> 119.2 24.00 0 17 0 0
#> 151.2 24.00 0 42 0 0
#> 53.1 24.00 0 32 0 1
#> 160 24.00 0 31 1 0
#> 191.2 24.00 0 60 0 1
#> 138 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 64 24.00 0 43 0 0
#> 121.2 24.00 0 57 1 0
#> 174 24.00 0 49 1 0
#> 53.2 24.00 0 32 0 1
#> 116.1 24.00 0 58 0 1
#> 104 24.00 0 50 1 0
#> 28.2 24.00 0 67 1 0
#> 71 24.00 0 51 0 0
#> 198 24.00 0 66 0 1
#> 35.1 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 135 24.00 0 58 1 0
#> 20.1 24.00 0 46 1 0
#> 120 24.00 0 68 0 1
#> 160.1 24.00 0 31 1 0
#> 174.1 24.00 0 49 1 0
#> 48 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 174.2 24.00 0 49 1 0
#> 94.1 24.00 0 51 0 1
#> 27.1 24.00 0 63 1 0
#> 115.1 24.00 0 NA 1 0
#> 74 24.00 0 43 0 1
#> 71.1 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 151.3 24.00 0 42 0 0
#> 147.1 24.00 0 76 1 0
#> 143.1 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.124 NA NA NA
#> 2 age, Cure model -0.00218 NA NA NA
#> 3 grade_ii, Cure model -0.0485 NA NA NA
#> 4 grade_iii, Cure model 0.607 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00363 NA NA NA
#> 2 grade_ii, Survival model 0.775 NA NA NA
#> 3 grade_iii, Survival model 0.444 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.123929 -0.002178 -0.048470 0.606849
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 256.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.123929467 -0.002177972 -0.048470373 0.606849003
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003631626 0.774761293 0.443750974
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.05931002 0.24837911 0.48299876 0.62817534 0.96319708 0.61223754
#> [7] 0.57926566 0.77170379 0.93037809 0.78482067 0.91369946 0.87270844
#> [13] 0.52881806 0.33665488 0.47335093 0.27935292 0.14172313 0.95230297
#> [19] 0.68878240 0.57926566 0.87270844 0.78482067 0.74445251 0.89636450
#> [25] 0.37610563 0.14172313 0.68878240 0.62817534 0.64352536 0.96859833
#> [31] 0.84214165 0.93037809 0.65885287 0.61223754 0.42312272 0.56258413
#> [37] 0.68878240 0.55413905 0.57926566 0.60397652 0.85456666 0.93037809
#> [43] 0.73045042 0.91369946 0.68139496 0.49259991 0.82355141 0.30988569
#> [49] 0.82355141 0.30988569 0.49259991 0.66641042 0.56258413 0.36304385
#> [55] 0.85456666 0.51103044 0.42312272 0.88455572 0.52881806 0.52881806
#> [61] 0.68878240 0.78482067 0.05931002 0.86669393 0.51103044 0.89636450
#> [67] 0.75822195 0.65123301 0.33665488 0.46332739 0.98441930 0.67394001
#> [73] 0.99483682 0.45313411 0.88455572 0.75822195 0.05931002 0.78482067
#> [79] 0.97916301 0.73750597 0.81067578 0.38880498 0.18913826 0.84214165
#> [85] 0.82355141 0.40080367 0.91369946 0.23041636 0.27935292 0.90793200
#> [91] 0.42312272 0.98964801 0.96859833 0.77170379 0.05931002 0.68878240
#> [97] 0.41221227 0.81067578 0.94680094 0.24837911 0.95777710 0.68878240
#> [103] 0.75134491 0.21140779 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 24 92 105 41 101 51 8 18 159 157 107 42 76
#> 23.89 22.92 19.75 18.02 9.97 18.23 18.43 15.21 10.55 15.10 11.18 12.43 19.22
#> 169 158 113 78 52 85 8.1 42.1 157.1 188 49 136 78.1
#> 22.41 20.14 22.86 23.88 10.42 16.44 18.43 12.43 15.10 16.16 12.19 21.83 23.88
#> 85.1 41.1 184 183 14 159.1 117 51.1 36 179 192 97 8.2
#> 16.44 18.02 17.77 9.24 12.89 10.55 17.46 18.23 21.19 18.63 16.44 19.14 18.43
#> 108 140 159.2 5 107.1 181 170 60 63 60.1 63.1 170.1 30
#> 18.29 12.68 10.55 16.43 11.18 16.46 19.54 13.15 22.77 13.15 22.77 19.54 17.43
#> 179.1 194 140.1 55 99 56 76.1 76.2 85.2 157.2 24.1 37 55.1
#> 18.63 22.40 12.68 19.34 21.19 12.21 19.22 19.22 16.44 15.10 23.89 12.52 19.34
#> 49.1 26 110 169.1 128 77 45 127 68 56.1 26.1 24.2 157.3
#> 12.19 15.77 17.56 22.41 20.35 7.27 17.42 3.53 20.62 12.21 15.77 23.89 15.10
#> 70 79 96 197 164 14.1 60.2 139 107.2 69 113.1 43 36.1
#> 7.38 16.23 14.54 21.60 23.60 12.89 13.15 21.49 11.18 23.23 22.86 12.10 21.19
#> 25 183.1 18.1 24.3 192.1 153 96.1 10 92.1 145 85.3 100 129
#> 6.32 9.24 15.21 23.89 16.44 21.33 14.54 10.53 22.92 10.07 16.44 16.07 23.41
#> 19 119 82 12 193 151 103 2 28 142 28.1 46 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 20 19.1 27 103.1 87 121 182 75 119.1 141 191 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 173 35 162 151.1 80 31 148 122 1 46.1 95 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.1 147 143 83 165 191.1 3 121.1 186 94 3.1 119.2 151.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 160 191.2 138 116 64 121.2 174 53.2 116.1 104 28.2 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 35.1 17 135 20.1 120 160.1 174.1 48 21 126 174.2 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 74 71.1 84 151.3 147.1 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[86]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.00270652 0.75980373 0.32913665
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.55137710 0.02911971 -0.10837905
#> grade_iii, Cure model
#> 1.40376095
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 29 15.45 1 68 1 0
#> 40 18.00 1 28 1 0
#> 16 8.71 1 71 0 1
#> 145 10.07 1 65 1 0
#> 90 20.94 1 50 0 1
#> 150 20.33 1 48 0 0
#> 111 17.45 1 47 0 1
#> 179 18.63 1 42 0 0
#> 50 10.02 1 NA 1 0
#> 90.1 20.94 1 50 0 1
#> 29.1 15.45 1 68 1 0
#> 15 22.68 1 48 0 0
#> 183 9.24 1 67 1 0
#> 55 19.34 1 69 0 1
#> 41 18.02 1 40 1 0
#> 124 9.73 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 55.1 19.34 1 69 0 1
#> 134 17.81 1 47 1 0
#> 61 10.12 1 36 0 1
#> 79 16.23 1 54 1 0
#> 45 17.42 1 54 0 1
#> 168 23.72 1 70 0 0
#> 187 9.92 1 39 1 0
#> 5 16.43 1 51 0 1
#> 149 8.37 1 33 1 0
#> 58 19.34 1 39 0 0
#> 170 19.54 1 43 0 1
#> 188 16.16 1 46 0 1
#> 107 11.18 1 54 1 0
#> 23 16.92 1 61 0 0
#> 37 12.52 1 57 1 0
#> 4 17.64 1 NA 0 1
#> 114 13.68 1 NA 0 0
#> 37.1 12.52 1 57 1 0
#> 89 11.44 1 NA 0 0
#> 51 18.23 1 83 0 1
#> 101 9.97 1 10 0 1
#> 36 21.19 1 48 0 1
#> 23.1 16.92 1 61 0 0
#> 125 15.65 1 67 1 0
#> 134.1 17.81 1 47 1 0
#> 181 16.46 1 45 0 1
#> 43 12.10 1 61 0 1
#> 57 14.46 1 45 0 1
#> 42 12.43 1 49 0 1
#> 76 19.22 1 54 0 1
#> 68 20.62 1 44 0 0
#> 187.1 9.92 1 39 1 0
#> 29.2 15.45 1 68 1 0
#> 128 20.35 1 35 0 1
#> 69 23.23 1 25 0 1
#> 108 18.29 1 39 0 1
#> 100 16.07 1 60 0 0
#> 157 15.10 1 47 0 0
#> 127 3.53 1 62 0 1
#> 42.1 12.43 1 49 0 1
#> 86 23.81 1 58 0 1
#> 140 12.68 1 59 1 0
#> 81 14.06 1 34 0 0
#> 85 16.44 1 36 0 0
#> 168.1 23.72 1 70 0 0
#> 153 21.33 1 55 1 0
#> 123 13.00 1 44 1 0
#> 32 20.90 1 37 1 0
#> 39 15.59 1 37 0 1
#> 157.1 15.10 1 47 0 0
#> 192 16.44 1 31 1 0
#> 113 22.86 1 34 0 0
#> 157.2 15.10 1 47 0 0
#> 181.1 16.46 1 45 0 1
#> 166 19.98 1 48 0 0
#> 51.1 18.23 1 83 0 1
#> 99 21.19 1 38 0 1
#> 76.1 19.22 1 54 0 1
#> 158 20.14 1 74 1 0
#> 69.1 23.23 1 25 0 1
#> 45.1 17.42 1 54 0 1
#> 32.1 20.90 1 37 1 0
#> 171 16.57 1 41 0 1
#> 96 14.54 1 33 0 1
#> 90.2 20.94 1 50 0 1
#> 93 10.33 1 52 0 1
#> 150.1 20.33 1 48 0 0
#> 97 19.14 1 65 0 1
#> 140.1 12.68 1 59 1 0
#> 42.2 12.43 1 49 0 1
#> 56 12.21 1 60 0 0
#> 15.1 22.68 1 48 0 0
#> 77 7.27 1 67 0 1
#> 168.2 23.72 1 70 0 0
#> 61.1 10.12 1 36 0 1
#> 171.1 16.57 1 41 0 1
#> 69.2 23.23 1 25 0 1
#> 51.2 18.23 1 83 0 1
#> 100.1 16.07 1 60 0 0
#> 68.1 20.62 1 44 0 0
#> 128.1 20.35 1 35 0 1
#> 157.3 15.10 1 47 0 0
#> 60 13.15 1 38 1 0
#> 26 15.77 1 49 0 1
#> 153.1 21.33 1 55 1 0
#> 188.1 16.16 1 46 0 1
#> 42.3 12.43 1 49 0 1
#> 190 20.81 1 42 1 0
#> 127.1 3.53 1 62 0 1
#> 55.2 19.34 1 69 0 1
#> 23.2 16.92 1 61 0 0
#> 85.1 16.44 1 36 0 0
#> 25 6.32 1 34 1 0
#> 79.1 16.23 1 54 1 0
#> 76.2 19.22 1 54 0 1
#> 160 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 7 24.00 0 37 1 0
#> 87 24.00 0 27 0 0
#> 178 24.00 0 52 1 0
#> 156 24.00 0 50 1 0
#> 7.1 24.00 0 37 1 0
#> 163 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 67 24.00 0 25 0 0
#> 165 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 112 24.00 0 61 0 0
#> 34 24.00 0 36 0 0
#> 62 24.00 0 71 0 0
#> 196 24.00 0 19 0 0
#> 48 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 62.1 24.00 0 71 0 0
#> 28 24.00 0 67 1 0
#> 87.1 24.00 0 27 0 0
#> 75 24.00 0 21 1 0
#> 185 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 67.1 24.00 0 25 0 0
#> 143 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 27 24.00 0 63 1 0
#> 46 24.00 0 71 0 0
#> 54.1 24.00 0 53 1 0
#> 48.1 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 144 24.00 0 28 0 1
#> 1 24.00 0 23 1 0
#> 20 24.00 0 46 1 0
#> 46.1 24.00 0 71 0 0
#> 84 24.00 0 39 0 1
#> 82.1 24.00 0 34 0 0
#> 20.1 24.00 0 46 1 0
#> 138 24.00 0 44 1 0
#> 75.1 24.00 0 21 1 0
#> 137 24.00 0 45 1 0
#> 162 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 173 24.00 0 19 0 1
#> 198 24.00 0 66 0 1
#> 144.1 24.00 0 28 0 1
#> 115 24.00 0 NA 1 0
#> 120 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 31 24.00 0 36 0 1
#> 1.1 24.00 0 23 1 0
#> 47.1 24.00 0 38 0 1
#> 176 24.00 0 43 0 1
#> 7.2 24.00 0 37 1 0
#> 102 24.00 0 49 0 0
#> 178.1 24.00 0 52 1 0
#> 83 24.00 0 6 0 0
#> 33 24.00 0 53 0 0
#> 44 24.00 0 56 0 0
#> 200 24.00 0 64 0 0
#> 186.1 24.00 0 45 1 0
#> 156.1 24.00 0 50 1 0
#> 1.2 24.00 0 23 1 0
#> 146 24.00 0 63 1 0
#> 178.2 24.00 0 52 1 0
#> 62.2 24.00 0 71 0 0
#> 186.2 24.00 0 45 1 0
#> 196.1 24.00 0 19 0 0
#> 141 24.00 0 44 1 0
#> 156.2 24.00 0 50 1 0
#> 196.2 24.00 0 19 0 0
#> 3 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 3.1 24.00 0 31 1 0
#> 186.3 24.00 0 45 1 0
#> 161 24.00 0 45 0 0
#> 64 24.00 0 43 0 0
#> 126 24.00 0 48 0 0
#> 121.1 24.00 0 57 1 0
#> 147 24.00 0 76 1 0
#> 103 24.00 0 56 1 0
#> 3.2 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 193 24.00 0 45 0 1
#> 95 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.55 NA NA NA
#> 2 age, Cure model 0.0291 NA NA NA
#> 3 grade_ii, Cure model -0.108 NA NA NA
#> 4 grade_iii, Cure model 1.40 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00271 NA NA NA
#> 2 grade_ii, Survival model 0.760 NA NA NA
#> 3 grade_iii, Survival model 0.329 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.55138 0.02912 -0.10838 1.40376
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.3
#> Residual Deviance: 238.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.55137710 0.02911971 -0.10837905 1.40376095
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.00270652 0.75980373 0.32913665
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.78054080 0.58199611 0.96741053 0.93934770 0.29612344 0.40772714
#> [7] 0.60596902 0.53045165 0.29612344 0.78054080 0.20699070 0.96187149
#> [13] 0.45814517 0.57360413 0.77380270 0.45814517 0.59023295 0.92788266
#> [19] 0.71113359 0.61382940 0.07826168 0.95072527 0.70381870 0.97292796
#> [25] 0.45814517 0.44828544 0.72526185 0.91628377 0.62921136 0.86923064
#> [31] 0.86923064 0.54829036 0.94504381 0.26943052 0.62921136 0.76011691
#> [37] 0.59023295 0.66707654 0.91041855 0.83169261 0.88117374 0.49470409
#> [43] 0.36571519 0.95072527 0.78054080 0.38702180 0.13855880 0.53941115
#> [49] 0.73923389 0.79980470 0.98927461 0.88117374 0.04231099 0.85703718
#> [55] 0.83808133 0.68196749 0.07826168 0.24116944 0.85078397 0.33242191
#> [61] 0.76697617 0.79980470 0.68196749 0.18870051 0.79980470 0.66707654
#> [67] 0.43830248 0.54829036 0.26943052 0.49470409 0.42828789 0.13855880
#> [73] 0.61382940 0.33242191 0.65199378 0.82527581 0.29612344 0.92209416
#> [79] 0.40772714 0.52147390 0.85703718 0.88117374 0.90452908 0.20699070
#> [85] 0.97840385 0.07826168 0.92788266 0.65199378 0.13855880 0.54829036
#> [91] 0.73923389 0.36571519 0.38702180 0.79980470 0.84446535 0.75315953
#> [97] 0.24116944 0.72526185 0.88117374 0.35482075 0.98927461 0.45814517
#> [103] 0.62921136 0.68196749 0.98385941 0.71113359 0.49470409 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 29 40 16 145 90 150 111 179 90.1 29.1 15 183 55
#> 15.45 18.00 8.71 10.07 20.94 20.33 17.45 18.63 20.94 15.45 22.68 9.24 19.34
#> 41 167 55.1 134 61 79 45 168 187 5 149 58 170
#> 18.02 15.55 19.34 17.81 10.12 16.23 17.42 23.72 9.92 16.43 8.37 19.34 19.54
#> 188 107 23 37 37.1 51 101 36 23.1 125 134.1 181 43
#> 16.16 11.18 16.92 12.52 12.52 18.23 9.97 21.19 16.92 15.65 17.81 16.46 12.10
#> 57 42 76 68 187.1 29.2 128 69 108 100 157 127 42.1
#> 14.46 12.43 19.22 20.62 9.92 15.45 20.35 23.23 18.29 16.07 15.10 3.53 12.43
#> 86 140 81 85 168.1 153 123 32 39 157.1 192 113 157.2
#> 23.81 12.68 14.06 16.44 23.72 21.33 13.00 20.90 15.59 15.10 16.44 22.86 15.10
#> 181.1 166 51.1 99 76.1 158 69.1 45.1 32.1 171 96 90.2 93
#> 16.46 19.98 18.23 21.19 19.22 20.14 23.23 17.42 20.90 16.57 14.54 20.94 10.33
#> 150.1 97 140.1 42.2 56 15.1 77 168.2 61.1 171.1 69.2 51.2 100.1
#> 20.33 19.14 12.68 12.43 12.21 22.68 7.27 23.72 10.12 16.57 23.23 18.23 16.07
#> 68.1 128.1 157.3 60 26 153.1 188.1 42.3 190 127.1 55.2 23.2 85.1
#> 20.62 20.35 15.10 13.15 15.77 21.33 16.16 12.43 20.81 3.53 19.34 16.92 16.44
#> 25 79.1 76.2 160 47 142 7 87 178 156 7.1 163 19
#> 6.32 16.23 19.22 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 165 131 112 34 62 196 48 65 62.1 28 87.1 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 121 186 67.1 143 54 27 46 54.1 48.1 82 144 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 46.1 84 82.1 20.1 138 75.1 137 162 152 173 198 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 53 31 1.1 47.1 176 7.2 102 178.1 83 33 44 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.1 156.1 1.2 146 178.2 62.2 186.2 196.1 141 156.2 196.2 3 3.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.3 161 64 126 121.1 147 103 3.2 174 193 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[87]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01300662 0.75249389 0.22090693
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.97752335 0.02040954 -0.17427957
#> grade_iii, Cure model
#> 0.91278897
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 77 7.27 1 67 0 1
#> 187 9.92 1 39 1 0
#> 170 19.54 1 43 0 1
#> 59 10.16 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 50 10.02 1 NA 1 0
#> 77.1 7.27 1 67 0 1
#> 125.1 15.65 1 67 1 0
#> 66 22.13 1 53 0 0
#> 5 16.43 1 51 0 1
#> 39 15.59 1 37 0 1
#> 77.2 7.27 1 67 0 1
#> 133 14.65 1 57 0 0
#> 69 23.23 1 25 0 1
#> 57 14.46 1 45 0 1
#> 108 18.29 1 39 0 1
#> 69.1 23.23 1 25 0 1
#> 134 17.81 1 47 1 0
#> 180 14.82 1 37 0 0
#> 110 17.56 1 65 0 1
#> 5.1 16.43 1 51 0 1
#> 10 10.53 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 92 22.92 1 47 0 1
#> 134.1 17.81 1 47 1 0
#> 55 19.34 1 69 0 1
#> 194.1 22.40 1 38 0 1
#> 15 22.68 1 48 0 0
#> 18 15.21 1 49 1 0
#> 170.1 19.54 1 43 0 1
#> 37 12.52 1 57 1 0
#> 57.1 14.46 1 45 0 1
#> 45 17.42 1 54 0 1
#> 192 16.44 1 31 1 0
#> 157 15.10 1 47 0 0
#> 91 5.33 1 61 0 1
#> 136 21.83 1 43 0 1
#> 81 14.06 1 34 0 0
#> 154 12.63 1 20 1 0
#> 155 13.08 1 26 0 0
#> 100 16.07 1 60 0 0
#> 66.1 22.13 1 53 0 0
#> 149 8.37 1 33 1 0
#> 69.2 23.23 1 25 0 1
#> 166 19.98 1 48 0 0
#> 100.1 16.07 1 60 0 0
#> 77.3 7.27 1 67 0 1
#> 179 18.63 1 42 0 0
#> 70 7.38 1 30 1 0
#> 24 23.89 1 38 0 0
#> 136.1 21.83 1 43 0 1
#> 117 17.46 1 26 0 1
#> 136.2 21.83 1 43 0 1
#> 61 10.12 1 36 0 1
#> 36 21.19 1 48 0 1
#> 10.1 10.53 1 34 0 0
#> 194.2 22.40 1 38 0 1
#> 37.1 12.52 1 57 1 0
#> 57.2 14.46 1 45 0 1
#> 110.1 17.56 1 65 0 1
#> 37.2 12.52 1 57 1 0
#> 23 16.92 1 61 0 0
#> 140 12.68 1 59 1 0
#> 184 17.77 1 38 0 0
#> 49 12.19 1 48 1 0
#> 130 16.47 1 53 0 1
#> 197 21.60 1 69 1 0
#> 169 22.41 1 46 0 0
#> 177 12.53 1 75 0 0
#> 150 20.33 1 48 0 0
#> 183 9.24 1 67 1 0
#> 130.1 16.47 1 53 0 1
#> 42 12.43 1 49 0 1
#> 37.3 12.52 1 57 1 0
#> 10.2 10.53 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 55.1 19.34 1 69 0 1
#> 188 16.16 1 46 0 1
#> 194.3 22.40 1 38 0 1
#> 195 11.76 1 NA 1 0
#> 150.1 20.33 1 48 0 0
#> 37.4 12.52 1 57 1 0
#> 128 20.35 1 35 0 1
#> 111 17.45 1 47 0 1
#> 24.1 23.89 1 38 0 0
#> 61.1 10.12 1 36 0 1
#> 76 19.22 1 54 0 1
#> 91.1 5.33 1 61 0 1
#> 133.1 14.65 1 57 0 0
#> 23.1 16.92 1 61 0 0
#> 158 20.14 1 74 1 0
#> 190 20.81 1 42 1 0
#> 171 16.57 1 41 0 1
#> 93 10.33 1 52 0 1
#> 25 6.32 1 34 1 0
#> 59.1 10.16 1 NA 1 0
#> 179.1 18.63 1 42 0 0
#> 4 17.64 1 NA 0 1
#> 32 20.90 1 37 1 0
#> 39.1 15.59 1 37 0 1
#> 78 23.88 1 43 0 0
#> 85 16.44 1 36 0 0
#> 106 16.67 1 49 1 0
#> 18.1 15.21 1 49 1 0
#> 181 16.46 1 45 0 1
#> 61.2 10.12 1 36 0 1
#> 158.1 20.14 1 74 1 0
#> 40 18.00 1 28 1 0
#> 128.1 20.35 1 35 0 1
#> 187.1 9.92 1 39 1 0
#> 86 23.81 1 58 0 1
#> 141 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 38 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 47 24.00 0 38 0 1
#> 137 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 135.1 24.00 0 58 1 0
#> 173 24.00 0 19 0 1
#> 54 24.00 0 53 1 0
#> 31 24.00 0 36 0 1
#> 152 24.00 0 36 0 1
#> 156 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 71 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 80 24.00 0 41 0 0
#> 161 24.00 0 45 0 0
#> 160 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 31.1 24.00 0 36 0 1
#> 119 24.00 0 17 0 0
#> 12 24.00 0 63 0 0
#> 84 24.00 0 39 0 1
#> 67 24.00 0 25 0 0
#> 132 24.00 0 55 0 0
#> 54.1 24.00 0 53 1 0
#> 193 24.00 0 45 0 1
#> 72 24.00 0 40 0 1
#> 200 24.00 0 64 0 0
#> 22 24.00 0 52 1 0
#> 64 24.00 0 43 0 0
#> 173.1 24.00 0 19 0 1
#> 84.1 24.00 0 39 0 1
#> 73.1 24.00 0 NA 0 1
#> 73.2 24.00 0 NA 0 1
#> 196 24.00 0 19 0 0
#> 193.1 24.00 0 45 0 1
#> 173.2 24.00 0 19 0 1
#> 82 24.00 0 34 0 0
#> 48 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 95 24.00 0 68 0 1
#> 151 24.00 0 42 0 0
#> 98 24.00 0 34 1 0
#> 74 24.00 0 43 0 1
#> 38.1 24.00 0 31 1 0
#> 98.1 24.00 0 34 1 0
#> 116 24.00 0 58 0 1
#> 121.1 24.00 0 57 1 0
#> 71.1 24.00 0 51 0 0
#> 71.2 24.00 0 51 0 0
#> 33 24.00 0 53 0 0
#> 174 24.00 0 49 1 0
#> 138 24.00 0 44 1 0
#> 12.1 24.00 0 63 0 0
#> 103 24.00 0 56 1 0
#> 72.1 24.00 0 40 0 1
#> 121.2 24.00 0 57 1 0
#> 83 24.00 0 6 0 0
#> 185 24.00 0 44 1 0
#> 3.1 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 182 24.00 0 35 0 0
#> 112 24.00 0 61 0 0
#> 54.2 24.00 0 53 1 0
#> 118 24.00 0 44 1 0
#> 173.3 24.00 0 19 0 1
#> 75 24.00 0 21 1 0
#> 178 24.00 0 52 1 0
#> 120 24.00 0 68 0 1
#> 131.1 24.00 0 66 0 0
#> 174.1 24.00 0 49 1 0
#> 137.1 24.00 0 45 1 0
#> 3.2 24.00 0 31 1 0
#> 64.1 24.00 0 43 0 0
#> 44 24.00 0 56 0 0
#> 112.1 24.00 0 61 0 0
#> 64.2 24.00 0 43 0 0
#> 165 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 135.2 24.00 0 58 1 0
#> 95.1 24.00 0 68 0 1
#> 47.1 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 160.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.978 NA NA NA
#> 2 age, Cure model 0.0204 NA NA NA
#> 3 grade_ii, Cure model -0.174 NA NA NA
#> 4 grade_iii, Cure model 0.913 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0130 NA NA NA
#> 2 grade_ii, Survival model 0.752 NA NA NA
#> 3 grade_iii, Survival model 0.221 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.97752 0.02041 -0.17428 0.91279
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 259.7
#> Residual Deviance: 246.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.97752335 0.02040954 -0.17427957 0.91278897
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01300662 0.75249389 0.22090693
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.37594126 0.97485428 0.95580921 0.61287263 0.81327172 0.97485428
#> [7] 0.81327172 0.43592138 0.78601666 0.82347475 0.97485428 0.85295797
#> [13] 0.24922564 0.86248076 0.66655310 0.24922564 0.68106474 0.84812374
#> [19] 0.70123776 0.78601666 0.92798569 0.31471054 0.68106474 0.62895831
#> [25] 0.37594126 0.33617317 0.83355069 0.61287263 0.89934418 0.86248076
#> [31] 0.72694276 0.77477148 0.84327242 0.99290135 0.46496603 0.87643971
#> [37] 0.89032634 0.88110378 0.80251925 0.43592138 0.96733874 0.24922564
#> [43] 0.60451536 0.80251925 0.97485428 0.65178859 0.97111203 0.09743968
#> [49] 0.46496603 0.71414152 0.46496603 0.94400839 0.51555292 0.92798569
#> [55] 0.37594126 0.89934418 0.86248076 0.70123776 0.89934418 0.73322305
#> [61] 0.88575793 0.69451936 0.92393132 0.75742905 0.50363562 0.35651087
#> [67] 0.89485403 0.56840218 0.96353189 0.75742905 0.91982355 0.89934418
#> [73] 0.92798569 0.62895831 0.79703777 0.37594126 0.56840218 0.89934418
#> [79] 0.54850181 0.72057905 0.09743968 0.94400839 0.64423905 0.99290135
#> [85] 0.85295797 0.73322305 0.58771642 0.53809142 0.75147965 0.94000847
#> [91] 0.98930032 0.65178859 0.52711517 0.82347475 0.17933596 0.77477148
#> [97] 0.74547674 0.83355069 0.76901200 0.94400839 0.58771642 0.67388917
#> [103] 0.54850181 0.95580921 0.21879794 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 194 77 187 170 125 77.1 125.1 66 5 39 77.2 133 69
#> 22.40 7.27 9.92 19.54 15.65 7.27 15.65 22.13 16.43 15.59 7.27 14.65 23.23
#> 57 108 69.1 134 180 110 5.1 10 92 134.1 55 194.1 15
#> 14.46 18.29 23.23 17.81 14.82 17.56 16.43 10.53 22.92 17.81 19.34 22.40 22.68
#> 18 170.1 37 57.1 45 192 157 91 136 81 154 155 100
#> 15.21 19.54 12.52 14.46 17.42 16.44 15.10 5.33 21.83 14.06 12.63 13.08 16.07
#> 66.1 149 69.2 166 100.1 77.3 179 70 24 136.1 117 136.2 61
#> 22.13 8.37 23.23 19.98 16.07 7.27 18.63 7.38 23.89 21.83 17.46 21.83 10.12
#> 36 10.1 194.2 37.1 57.2 110.1 37.2 23 140 184 49 130 197
#> 21.19 10.53 22.40 12.52 14.46 17.56 12.52 16.92 12.68 17.77 12.19 16.47 21.60
#> 169 177 150 183 130.1 42 37.3 10.2 55.1 188 194.3 150.1 37.4
#> 22.41 12.53 20.33 9.24 16.47 12.43 12.52 10.53 19.34 16.16 22.40 20.33 12.52
#> 128 111 24.1 61.1 76 91.1 133.1 23.1 158 190 171 93 25
#> 20.35 17.45 23.89 10.12 19.22 5.33 14.65 16.92 20.14 20.81 16.57 10.33 6.32
#> 179.1 32 39.1 78 85 106 18.1 181 61.2 158.1 40 128.1 187.1
#> 18.63 20.90 15.59 23.88 16.44 16.67 15.21 16.46 10.12 20.14 18.00 20.35 9.92
#> 86 141 7 38 135 47 137 27 35 131 135.1 173 54
#> 23.81 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 152 156 121 71 80 161 160 3 31.1 119 12 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 132 54.1 193 72 200 22 64 173.1 84.1 196 193.1 173.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 48 87 95 151 98 74 38.1 98.1 116 121.1 71.1 71.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 174 138 12.1 103 72.1 121.2 83 185 3.1 198 182 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.2 118 173.3 75 178 120 131.1 174.1 137.1 3.2 64.1 44 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.2 165 135.2 95.1 47.1 143 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[88]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.008168965 0.783307508 0.165582917
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.100820723 0.002840877 0.106534499
#> grade_iii, Cure model
#> 0.301272740
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 4 17.64 1 NA 0 1
#> 107 11.18 1 54 1 0
#> 180 14.82 1 37 0 0
#> 157 15.10 1 47 0 0
#> 92 22.92 1 47 0 1
#> 183 9.24 1 67 1 0
#> 52 10.42 1 52 0 1
#> 30 17.43 1 78 0 0
#> 171 16.57 1 41 0 1
#> 199 19.81 1 NA 0 1
#> 180.1 14.82 1 37 0 0
#> 195 11.76 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 171.1 16.57 1 41 0 1
#> 108 18.29 1 39 0 1
#> 24 23.89 1 38 0 0
#> 10 10.53 1 34 0 0
#> 184 17.77 1 38 0 0
#> 127 3.53 1 62 0 1
#> 68 20.62 1 44 0 0
#> 194 22.40 1 38 0 1
#> 57 14.46 1 45 0 1
#> 24.1 23.89 1 38 0 0
#> 77 7.27 1 67 0 1
#> 92.1 22.92 1 47 0 1
#> 164 23.60 1 76 0 1
#> 124 9.73 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 150 20.33 1 48 0 0
#> 194.1 22.40 1 38 0 1
#> 159 10.55 1 50 0 1
#> 125 15.65 1 67 1 0
#> 101 9.97 1 10 0 1
#> 117 17.46 1 26 0 1
#> 157.1 15.10 1 47 0 0
#> 60 13.15 1 38 1 0
#> 68.1 20.62 1 44 0 0
#> 32 20.90 1 37 1 0
#> 139 21.49 1 63 1 0
#> 57.1 14.46 1 45 0 1
#> 76 19.22 1 54 0 1
#> 169 22.41 1 46 0 0
#> 113 22.86 1 34 0 0
#> 134 17.81 1 47 1 0
#> 108.1 18.29 1 39 0 1
#> 52.1 10.42 1 52 0 1
#> 78 23.88 1 43 0 0
#> 184.1 17.77 1 38 0 0
#> 89 11.44 1 NA 0 0
#> 18 15.21 1 49 1 0
#> 70 7.38 1 30 1 0
#> 123 13.00 1 44 1 0
#> 133 14.65 1 57 0 0
#> 70.1 7.38 1 30 1 0
#> 100 16.07 1 60 0 0
#> 43 12.10 1 61 0 1
#> 63 22.77 1 31 1 0
#> 89.1 11.44 1 NA 0 0
#> 61 10.12 1 36 0 1
#> 190 20.81 1 42 1 0
#> 79 16.23 1 54 1 0
#> 55 19.34 1 69 0 1
#> 167 15.55 1 56 1 0
#> 41 18.02 1 40 1 0
#> 29 15.45 1 68 1 0
#> 114 13.68 1 NA 0 0
#> 123.1 13.00 1 44 1 0
#> 59 10.16 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 157.2 15.10 1 47 0 0
#> 88 18.37 1 47 0 0
#> 167.1 15.55 1 56 1 0
#> 194.2 22.40 1 38 0 1
#> 100.1 16.07 1 60 0 0
#> 8 18.43 1 32 0 0
#> 88.1 18.37 1 47 0 0
#> 123.2 13.00 1 44 1 0
#> 81 14.06 1 34 0 0
#> 107.1 11.18 1 54 1 0
#> 166 19.98 1 48 0 0
#> 81.1 14.06 1 34 0 0
#> 42 12.43 1 49 0 1
#> 134.1 17.81 1 47 1 0
#> 123.3 13.00 1 44 1 0
#> 124.1 9.73 1 NA 1 0
#> 92.2 22.92 1 47 0 1
#> 184.2 17.77 1 38 0 0
#> 92.3 22.92 1 47 0 1
#> 24.2 23.89 1 38 0 0
#> 85 16.44 1 36 0 0
#> 39 15.59 1 37 0 1
#> 43.1 12.10 1 61 0 1
#> 133.1 14.65 1 57 0 0
#> 113.1 22.86 1 34 0 0
#> 169.1 22.41 1 46 0 0
#> 153 21.33 1 55 1 0
#> 110 17.56 1 65 0 1
#> 175 21.91 1 43 0 0
#> 188 16.16 1 46 0 1
#> 183.1 9.24 1 67 1 0
#> 15 22.68 1 48 0 0
#> 6 15.64 1 39 0 0
#> 177 12.53 1 75 0 0
#> 149.1 8.37 1 33 1 0
#> 155 13.08 1 26 0 0
#> 124.2 9.73 1 NA 1 0
#> 133.2 14.65 1 57 0 0
#> 187.1 9.92 1 39 1 0
#> 134.2 17.81 1 47 1 0
#> 110.1 17.56 1 65 0 1
#> 66 22.13 1 53 0 0
#> 89.2 11.44 1 NA 0 0
#> 143 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 74 24.00 0 43 0 1
#> 109 24.00 0 48 0 0
#> 122 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 2 24.00 0 9 0 0
#> 11 24.00 0 42 0 1
#> 198 24.00 0 66 0 1
#> 122.1 24.00 0 66 0 0
#> 112 24.00 0 61 0 0
#> 119 24.00 0 17 0 0
#> 2.1 24.00 0 9 0 0
#> 48 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 119.1 24.00 0 17 0 0
#> 22 24.00 0 52 1 0
#> 2.2 24.00 0 9 0 0
#> 84 24.00 0 39 0 1
#> 31 24.00 0 36 0 1
#> 173 24.00 0 19 0 1
#> 33 24.00 0 53 0 0
#> 2.3 24.00 0 9 0 0
#> 151 24.00 0 42 0 0
#> 53 24.00 0 32 0 1
#> 21 24.00 0 47 0 0
#> 147 24.00 0 76 1 0
#> 9 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 191.1 24.00 0 60 0 1
#> 46 24.00 0 71 0 0
#> 196 24.00 0 19 0 0
#> 156 24.00 0 50 1 0
#> 34 24.00 0 36 0 0
#> 138 24.00 0 44 1 0
#> 191.2 24.00 0 60 0 1
#> 71 24.00 0 51 0 0
#> 53.1 24.00 0 32 0 1
#> 17 24.00 0 38 0 1
#> 84.1 24.00 0 39 0 1
#> 104 24.00 0 50 1 0
#> 28 24.00 0 67 1 0
#> 19 24.00 0 57 0 1
#> 115 24.00 0 NA 1 0
#> 82 24.00 0 34 0 0
#> 135 24.00 0 58 1 0
#> 142 24.00 0 53 0 0
#> 31.1 24.00 0 36 0 1
#> 163 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 74.1 24.00 0 43 0 1
#> 146.1 24.00 0 63 1 0
#> 82.1 24.00 0 34 0 0
#> 144 24.00 0 28 0 1
#> 74.2 24.00 0 43 0 1
#> 165 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 22.1 24.00 0 52 1 0
#> 161 24.00 0 45 0 0
#> 104.1 24.00 0 50 1 0
#> 104.2 24.00 0 50 1 0
#> 141 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 137 24.00 0 45 1 0
#> 28.1 24.00 0 67 1 0
#> 9.1 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 191.3 24.00 0 60 0 1
#> 141.1 24.00 0 44 1 0
#> 35.1 24.00 0 51 0 0
#> 2.4 24.00 0 9 0 0
#> 156.1 24.00 0 50 1 0
#> 122.2 24.00 0 66 0 0
#> 21.1 24.00 0 47 0 0
#> 82.2 24.00 0 34 0 0
#> 19.1 24.00 0 57 0 1
#> 31.2 24.00 0 36 0 1
#> 17.1 24.00 0 38 0 1
#> 162 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 109.1 24.00 0 48 0 0
#> 12 24.00 0 63 0 0
#> 122.3 24.00 0 66 0 0
#> 46.1 24.00 0 71 0 0
#> 160 24.00 0 31 1 0
#> 71.1 24.00 0 51 0 0
#> 31.3 24.00 0 36 0 1
#> 162.1 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.101 NA NA NA
#> 2 age, Cure model 0.00284 NA NA NA
#> 3 grade_ii, Cure model 0.107 NA NA NA
#> 4 grade_iii, Cure model 0.301 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00817 NA NA NA
#> 2 grade_ii, Survival model 0.783 NA NA NA
#> 3 grade_iii, Survival model 0.166 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.100821 0.002841 0.106534 0.301273
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 258.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.100820723 0.002840877 0.106534499 0.301272740
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.008168965 0.783307508 0.165582917
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9085037 0.7969942 0.7783000 0.2241659 0.9611400 0.9298549 0.6722243
#> [8] 0.6798884 0.7969942 0.9710926 0.6798884 0.5742905 0.0707325 0.9245288
#> [15] 0.6253626 0.9952373 0.4870368 0.3779692 0.8277802 0.0707325 0.9904527
#> [22] 0.2241659 0.1765206 0.2009722 0.5070225 0.3779692 0.9191927 0.7313600
#> [29] 0.9456401 0.6644816 0.7783000 0.8520190 0.4870368 0.4659892 0.4427126
#> [36] 0.8277802 0.5366360 0.3499200 0.2874522 0.6013914 0.5742905 0.9298549
#> [43] 0.1472370 0.6253626 0.7719460 0.9808584 0.8639746 0.8094373 0.9808584
#> [50] 0.7170534 0.8975038 0.3198527 0.9403800 0.4767550 0.7024359 0.5269261
#> [57] 0.7522634 0.5924972 0.7654712 0.8639746 0.9508921 0.7783000 0.5557172
#> [64] 0.7522634 0.3779692 0.7170534 0.5462015 0.5557172 0.8639746 0.8399276
#> [71] 0.9085037 0.5170203 0.8399276 0.8919223 0.6013914 0.8639746 0.2241659
#> [78] 0.6253626 0.2241659 0.0707325 0.6949113 0.7453297 0.8975038 0.8094373
#> [85] 0.2874522 0.3499200 0.4547125 0.6490041 0.4297798 0.7097716 0.9611400
#> [92] 0.3350482 0.7383572 0.8863140 0.9710926 0.8580017 0.8094373 0.9508921
#> [99] 0.6013914 0.6490041 0.4166811 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 107 180 157 92 183 52 30 171 180.1 149 171.1 108 24
#> 11.18 14.82 15.10 22.92 9.24 10.42 17.43 16.57 14.82 8.37 16.57 18.29 23.89
#> 10 184 127 68 194 57 24.1 77 92.1 164 69 150 194.1
#> 10.53 17.77 3.53 20.62 22.40 14.46 23.89 7.27 22.92 23.60 23.23 20.33 22.40
#> 159 125 101 117 157.1 60 68.1 32 139 57.1 76 169 113
#> 10.55 15.65 9.97 17.46 15.10 13.15 20.62 20.90 21.49 14.46 19.22 22.41 22.86
#> 134 108.1 52.1 78 184.1 18 70 123 133 70.1 100 43 63
#> 17.81 18.29 10.42 23.88 17.77 15.21 7.38 13.00 14.65 7.38 16.07 12.10 22.77
#> 61 190 79 55 167 41 29 123.1 187 157.2 88 167.1 194.2
#> 10.12 20.81 16.23 19.34 15.55 18.02 15.45 13.00 9.92 15.10 18.37 15.55 22.40
#> 100.1 8 88.1 123.2 81 107.1 166 81.1 42 134.1 123.3 92.2 184.2
#> 16.07 18.43 18.37 13.00 14.06 11.18 19.98 14.06 12.43 17.81 13.00 22.92 17.77
#> 92.3 24.2 85 39 43.1 133.1 113.1 169.1 153 110 175 188 183.1
#> 22.92 23.89 16.44 15.59 12.10 14.65 22.86 22.41 21.33 17.56 21.91 16.16 9.24
#> 15 6 177 149.1 155 133.2 187.1 134.2 110.1 66 143 65 74
#> 22.68 15.64 12.53 8.37 13.08 14.65 9.92 17.81 17.56 22.13 24.00 24.00 24.00
#> 109 122 191 2 11 198 122.1 112 119 2.1 48 118 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 2.2 84 31 173 33 2.3 151 53 21 147 9 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 46 196 156 34 138 191.2 71 53.1 17 84.1 104 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 82 135 142 31.1 163 146 74.1 146.1 82.1 144 74.2 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 22.1 161 104.1 104.2 141 62 137 28.1 9.1 35 191.3 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.1 2.4 156.1 122.2 21.1 82.2 19.1 31.2 17.1 162 178 109.1 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.3 46.1 160 71.1 31.3 162.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[89]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01132684 0.36312371 0.11065727
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.70650641 0.01450712 0.22560658
#> grade_iii, Cure model
#> 0.41159412
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 105 19.75 1 60 0 0
#> 63 22.77 1 31 1 0
#> 101 9.97 1 10 0 1
#> 76 19.22 1 54 0 1
#> 180 14.82 1 37 0 0
#> 91 5.33 1 61 0 1
#> 81 14.06 1 34 0 0
#> 184 17.77 1 38 0 0
#> 66 22.13 1 53 0 0
#> 180.1 14.82 1 37 0 0
#> 29 15.45 1 68 1 0
#> 23 16.92 1 61 0 0
#> 59 10.16 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 187 9.92 1 39 1 0
#> 40 18.00 1 28 1 0
#> 49 12.19 1 48 1 0
#> 86 23.81 1 58 0 1
#> 60 13.15 1 38 1 0
#> 168 23.72 1 70 0 0
#> 45 17.42 1 54 0 1
#> 194 22.40 1 38 0 1
#> 179 18.63 1 42 0 0
#> 39 15.59 1 37 0 1
#> 177 12.53 1 75 0 0
#> 159 10.55 1 50 0 1
#> 85 16.44 1 36 0 0
#> 39.1 15.59 1 37 0 1
#> 6 15.64 1 39 0 0
#> 177.1 12.53 1 75 0 0
#> 157 15.10 1 47 0 0
#> 5 16.43 1 51 0 1
#> 42 12.43 1 49 0 1
#> 10 10.53 1 34 0 0
#> 50 10.02 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 55 19.34 1 69 0 1
#> 86.1 23.81 1 58 0 1
#> 175 21.91 1 43 0 0
#> 177.2 12.53 1 75 0 0
#> 10.1 10.53 1 34 0 0
#> 36 21.19 1 48 0 1
#> 59.1 10.16 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 184.1 17.77 1 38 0 0
#> 175.1 21.91 1 43 0 0
#> 26 15.77 1 49 0 1
#> 70 7.38 1 30 1 0
#> 197 21.60 1 69 1 0
#> 42.1 12.43 1 49 0 1
#> 111 17.45 1 47 0 1
#> 159.1 10.55 1 50 0 1
#> 30 17.43 1 78 0 0
#> 139 21.49 1 63 1 0
#> 101.1 9.97 1 10 0 1
#> 111.1 17.45 1 47 0 1
#> 181 16.46 1 45 0 1
#> 149 8.37 1 33 1 0
#> 114 13.68 1 NA 0 0
#> 66.1 22.13 1 53 0 0
#> 107 11.18 1 54 1 0
#> 68 20.62 1 44 0 0
#> 140 12.68 1 59 1 0
#> 51 18.23 1 83 0 1
#> 18 15.21 1 49 1 0
#> 158 20.14 1 74 1 0
#> 195 11.76 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 10.2 10.53 1 34 0 0
#> 50.1 10.02 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 85.1 16.44 1 36 0 0
#> 136 21.83 1 43 0 1
#> 155 13.08 1 26 0 0
#> 99 21.19 1 38 0 1
#> 60.1 13.15 1 38 1 0
#> 145.1 10.07 1 65 1 0
#> 88 18.37 1 47 0 0
#> 188 16.16 1 46 0 1
#> 197.1 21.60 1 69 1 0
#> 170 19.54 1 43 0 1
#> 123 13.00 1 44 1 0
#> 171 16.57 1 41 0 1
#> 171.1 16.57 1 41 0 1
#> 40.1 18.00 1 28 1 0
#> 175.2 21.91 1 43 0 0
#> 177.3 12.53 1 75 0 0
#> 49.1 12.19 1 48 1 0
#> 92 22.92 1 47 0 1
#> 60.2 13.15 1 38 1 0
#> 24 23.89 1 38 0 0
#> 79 16.23 1 54 1 0
#> 169 22.41 1 46 0 0
#> 45.1 17.42 1 54 0 1
#> 190 20.81 1 42 1 0
#> 181.1 16.46 1 45 0 1
#> 192 16.44 1 31 1 0
#> 66.2 22.13 1 53 0 0
#> 49.2 12.19 1 48 1 0
#> 39.2 15.59 1 37 0 1
#> 25 6.32 1 34 1 0
#> 93 10.33 1 52 0 1
#> 63.1 22.77 1 31 1 0
#> 129 23.41 1 53 1 0
#> 6.1 15.64 1 39 0 0
#> 32 20.90 1 37 1 0
#> 187.1 9.92 1 39 1 0
#> 52 10.42 1 52 0 1
#> 164 23.60 1 76 0 1
#> 25.1 6.32 1 34 1 0
#> 30.1 17.43 1 78 0 0
#> 50.2 10.02 1 NA 1 0
#> 196 24.00 0 19 0 0
#> 44 24.00 0 56 0 0
#> 19 24.00 0 57 0 1
#> 27 24.00 0 63 1 0
#> 20 24.00 0 46 1 0
#> 7 24.00 0 37 1 0
#> 47 24.00 0 38 0 1
#> 172 24.00 0 41 0 0
#> 109 24.00 0 48 0 0
#> 152 24.00 0 36 0 1
#> 21 24.00 0 47 0 0
#> 141 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 176 24.00 0 43 0 1
#> 156 24.00 0 50 1 0
#> 74 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 54 24.00 0 53 1 0
#> 21.1 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 94.1 24.00 0 51 0 1
#> 109.1 24.00 0 48 0 0
#> 22 24.00 0 52 1 0
#> 135 24.00 0 58 1 0
#> 118 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 74.1 24.00 0 43 0 1
#> 138 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 112 24.00 0 61 0 0
#> 53 24.00 0 32 0 1
#> 83 24.00 0 6 0 0
#> 102 24.00 0 49 0 0
#> 72 24.00 0 40 0 1
#> 2 24.00 0 9 0 0
#> 65.1 24.00 0 57 1 0
#> 173 24.00 0 19 0 1
#> 53.1 24.00 0 32 0 1
#> 67 24.00 0 25 0 0
#> 135.1 24.00 0 58 1 0
#> 54.1 24.00 0 53 1 0
#> 31 24.00 0 36 0 1
#> 163 24.00 0 66 0 0
#> 2.1 24.00 0 9 0 0
#> 112.1 24.00 0 61 0 0
#> 65.2 24.00 0 57 1 0
#> 19.1 24.00 0 57 0 1
#> 94.2 24.00 0 51 0 1
#> 160 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 112.2 24.00 0 61 0 0
#> 162 24.00 0 51 0 0
#> 7.1 24.00 0 37 1 0
#> 34 24.00 0 36 0 0
#> 162.1 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 19.2 24.00 0 57 0 1
#> 109.2 24.00 0 48 0 0
#> 84 24.00 0 39 0 1
#> 122 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 152.1 24.00 0 36 0 1
#> 9.1 24.00 0 31 1 0
#> 156.1 24.00 0 50 1 0
#> 126 24.00 0 48 0 0
#> 196.1 24.00 0 19 0 0
#> 19.3 24.00 0 57 0 1
#> 165 24.00 0 47 0 0
#> 19.4 24.00 0 57 0 1
#> 33 24.00 0 53 0 0
#> 48 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 148 24.00 0 61 1 0
#> 174 24.00 0 49 1 0
#> 182.1 24.00 0 35 0 0
#> 98 24.00 0 34 1 0
#> 62 24.00 0 71 0 0
#> 12 24.00 0 63 0 0
#> 62.1 24.00 0 71 0 0
#> 176.1 24.00 0 43 0 1
#> 176.2 24.00 0 43 0 1
#> 142 24.00 0 53 0 0
#> 31.1 24.00 0 36 0 1
#> 102.1 24.00 0 49 0 0
#> 82 24.00 0 34 0 0
#> 44.1 24.00 0 56 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.707 NA NA NA
#> 2 age, Cure model 0.0145 NA NA NA
#> 3 grade_ii, Cure model 0.226 NA NA NA
#> 4 grade_iii, Cure model 0.412 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0113 NA NA NA
#> 2 grade_ii, Survival model 0.363 NA NA NA
#> 3 grade_iii, Survival model 0.111 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.70651 0.01451 0.22561 0.41159
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 261.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.70650641 0.01450712 0.22560658 0.41159412
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01132684 0.36312371 0.11065727
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.1372007370 0.0209300324 0.8778860170 0.1602948404 0.5033420443
#> [6] 0.9862833487 0.5381278997 0.2100226121 0.0382344563 0.5033420443
#> [11] 0.4692147298 0.2819701165 0.8508888234 0.9048854411 0.1933705470
#> [16] 0.6949484449 0.0018290781 0.5499742591 0.0055276001 0.2630924793
#> [21] 0.0334750356 0.1683191730 0.4363594262 0.6208488927 0.7456766718
#> [26] 0.3313415651 0.4363594262 0.4146123130 0.6208488927 0.4918778842
#> [31] 0.3614880666 0.6697157002 0.7715525181 0.5263643189 0.1524257904
#> [36] 0.0018290781 0.0530350549 0.6208488927 0.7715525181 0.0951499923
#> [41] 0.4037977093 0.2100226121 0.0530350549 0.3930769617 0.9455780240
#> [46] 0.0758592511 0.6697157002 0.2271501295 0.7456766718 0.2447342667
#> [51] 0.0884608207 0.8778860170 0.2271501295 0.3113326643 0.9319459707
#> [56] 0.0382344563 0.7327896706 0.1226544623 0.6088135710 0.1848221667
#> [61] 0.4805229733 0.1298505490 0.8374156531 0.7715525181 0.3313415651
#> [66] 0.0696438321 0.5848977509 0.0951499923 0.5499742591 0.8508888234
#> [71] 0.1764910343 0.3824601103 0.0758592511 0.1447504477 0.5968405029
#> [76] 0.2917384107 0.2917384107 0.1933705470 0.0530350549 0.6208488927
#> [81] 0.6949484449 0.0164748656 0.5499742591 0.0003929429 0.3719415545
#> [86] 0.0288946146 0.2630924793 0.1156204190 0.3113326643 0.3313415651
#> [91] 0.0382344563 0.6949484449 0.4363594262 0.9592054457 0.8239979747
#> [96] 0.0209300324 0.0124026713 0.4146123130 0.1086317709 0.9048854411
#> [101] 0.8106628546 0.0086024319 0.9592054457 0.2447342667 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000 0.0000000000
#>
#> $Time
#> 105 63 101 76 180 91 81 184 66 180.1 29 23 145
#> 19.75 22.77 9.97 19.22 14.82 5.33 14.06 17.77 22.13 14.82 15.45 16.92 10.07
#> 187 40 49 86 60 168 45 194 179 39 177 159 85
#> 9.92 18.00 12.19 23.81 13.15 23.72 17.42 22.40 18.63 15.59 12.53 10.55 16.44
#> 39.1 6 177.1 157 5 42 10 133 55 86.1 175 177.2 10.1
#> 15.59 15.64 12.53 15.10 16.43 12.43 10.53 14.65 19.34 23.81 21.91 12.53 10.53
#> 36 125 184.1 175.1 26 70 197 42.1 111 159.1 30 139 101.1
#> 21.19 15.65 17.77 21.91 15.77 7.38 21.60 12.43 17.45 10.55 17.43 21.49 9.97
#> 111.1 181 149 66.1 107 68 140 51 18 158 61 10.2 85.1
#> 17.45 16.46 8.37 22.13 11.18 20.62 12.68 18.23 15.21 20.14 10.12 10.53 16.44
#> 136 155 99 60.1 145.1 88 188 197.1 170 123 171 171.1 40.1
#> 21.83 13.08 21.19 13.15 10.07 18.37 16.16 21.60 19.54 13.00 16.57 16.57 18.00
#> 175.2 177.3 49.1 92 60.2 24 79 169 45.1 190 181.1 192 66.2
#> 21.91 12.53 12.19 22.92 13.15 23.89 16.23 22.41 17.42 20.81 16.46 16.44 22.13
#> 49.2 39.2 25 93 63.1 129 6.1 32 187.1 52 164 25.1 30.1
#> 12.19 15.59 6.32 10.33 22.77 23.41 15.64 20.90 9.92 10.42 23.60 6.32 17.43
#> 196 44 19 27 20 7 47 172 109 152 21 141 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 156 74 185 17 54 21.1 94 94.1 109.1 22 135 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 74.1 138 119 112 53 83 102 72 2 65.1 173 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 135.1 54.1 31 163 2.1 112.1 65.2 19.1 94.2 160 160.1 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.2 162 7.1 34 162.1 182 19.2 109.2 84 122 147 152.1 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.1 126 196.1 19.3 165 19.4 33 48 193 148 174 182.1 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 12 62.1 176.1 176.2 142 31.1 102.1 82 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[90]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008119127 1.118191205 0.475185071
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.604500323 0.006135986 -0.101684777
#> grade_iii, Cure model
#> 1.367742805
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 159 10.55 1 50 0 1
#> 4 17.64 1 NA 0 1
#> 166 19.98 1 48 0 0
#> 25 6.32 1 34 1 0
#> 50 10.02 1 NA 1 0
#> 4.1 17.64 1 NA 0 1
#> 140 12.68 1 59 1 0
#> 117 17.46 1 26 0 1
#> 96 14.54 1 33 0 1
#> 199 19.81 1 NA 0 1
#> 166.1 19.98 1 48 0 0
#> 108 18.29 1 39 0 1
#> 10 10.53 1 34 0 0
#> 157 15.10 1 47 0 0
#> 93 10.33 1 52 0 1
#> 169 22.41 1 46 0 0
#> 77 7.27 1 67 0 1
#> 29 15.45 1 68 1 0
#> 25.1 6.32 1 34 1 0
#> 50.1 10.02 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 45 17.42 1 54 0 1
#> 111 17.45 1 47 0 1
#> 101 9.97 1 10 0 1
#> 189 10.51 1 NA 1 0
#> 108.1 18.29 1 39 0 1
#> 130 16.47 1 53 0 1
#> 39 15.59 1 37 0 1
#> 99 21.19 1 38 0 1
#> 154 12.63 1 20 1 0
#> 130.1 16.47 1 53 0 1
#> 154.1 12.63 1 20 1 0
#> 110 17.56 1 65 0 1
#> 188 16.16 1 46 0 1
#> 171 16.57 1 41 0 1
#> 113 22.86 1 34 0 0
#> 192 16.44 1 31 1 0
#> 194 22.40 1 38 0 1
#> 159.1 10.55 1 50 0 1
#> 113.1 22.86 1 34 0 0
#> 23 16.92 1 61 0 0
#> 4.2 17.64 1 NA 0 1
#> 26 15.77 1 49 0 1
#> 88 18.37 1 47 0 0
#> 25.2 6.32 1 34 1 0
#> 150 20.33 1 48 0 0
#> 49 12.19 1 48 1 0
#> 107 11.18 1 54 1 0
#> 96.1 14.54 1 33 0 1
#> 42 12.43 1 49 0 1
#> 77.1 7.27 1 67 0 1
#> 26.1 15.77 1 49 0 1
#> 45.1 17.42 1 54 0 1
#> 79 16.23 1 54 1 0
#> 50.2 10.02 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 61.1 10.12 1 36 0 1
#> 89 11.44 1 NA 0 0
#> 99.1 21.19 1 38 0 1
#> 50.3 10.02 1 NA 1 0
#> 61.2 10.12 1 36 0 1
#> 50.4 10.02 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 50.5 10.02 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 183 9.24 1 67 1 0
#> 128 20.35 1 35 0 1
#> 164 23.60 1 76 0 1
#> 111.1 17.45 1 47 0 1
#> 8 18.43 1 32 0 0
#> 92 22.92 1 47 0 1
#> 76 19.22 1 54 0 1
#> 14 12.89 1 21 0 0
#> 140.1 12.68 1 59 1 0
#> 133 14.65 1 57 0 0
#> 177 12.53 1 75 0 0
#> 26.2 15.77 1 49 0 1
#> 86 23.81 1 58 0 1
#> 8.1 18.43 1 32 0 0
#> 184 17.77 1 38 0 0
#> 166.2 19.98 1 48 0 0
#> 166.3 19.98 1 48 0 0
#> 139.1 21.49 1 63 1 0
#> 37 12.52 1 57 1 0
#> 97 19.14 1 65 0 1
#> 125 15.65 1 67 1 0
#> 77.2 7.27 1 67 0 1
#> 145 10.07 1 65 1 0
#> 24 23.89 1 38 0 0
#> 99.2 21.19 1 38 0 1
#> 97.1 19.14 1 65 0 1
#> 92.1 22.92 1 47 0 1
#> 175 21.91 1 43 0 0
#> 78 23.88 1 43 0 0
#> 85 16.44 1 36 0 0
#> 50.6 10.02 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 195.1 11.76 1 NA 1 0
#> 86.1 23.81 1 58 0 1
#> 50.7 10.02 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 58 19.34 1 39 0 0
#> 32 20.90 1 37 1 0
#> 127 3.53 1 62 0 1
#> 105 19.75 1 60 0 0
#> 106 16.67 1 49 1 0
#> 40 18.00 1 28 1 0
#> 45.2 17.42 1 54 0 1
#> 41 18.02 1 40 1 0
#> 89.1 11.44 1 NA 0 0
#> 140.2 12.68 1 59 1 0
#> 36 21.19 1 48 0 1
#> 28 24.00 0 67 1 0
#> 135 24.00 0 58 1 0
#> 104 24.00 0 50 1 0
#> 152 24.00 0 36 0 1
#> 122 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 44 24.00 0 56 0 0
#> 152.1 24.00 0 36 0 1
#> 126 24.00 0 48 0 0
#> 178 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 185 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 165 24.00 0 47 0 0
#> 141 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 103 24.00 0 56 1 0
#> 80 24.00 0 41 0 0
#> 122.1 24.00 0 66 0 0
#> 126.1 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 174 24.00 0 49 1 0
#> 98 24.00 0 34 1 0
#> 196 24.00 0 19 0 0
#> 200 24.00 0 64 0 0
#> 94 24.00 0 51 0 1
#> 116 24.00 0 58 0 1
#> 126.2 24.00 0 48 0 0
#> 21.1 24.00 0 47 0 0
#> 172 24.00 0 41 0 0
#> 53 24.00 0 32 0 1
#> 137 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 137.1 24.00 0 45 1 0
#> 143 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 75 24.00 0 21 1 0
#> 165.1 24.00 0 47 0 0
#> 12.1 24.00 0 63 0 0
#> 27.1 24.00 0 63 1 0
#> 182 24.00 0 35 0 0
#> 20.1 24.00 0 46 1 0
#> 118 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 54 24.00 0 53 1 0
#> 12.2 24.00 0 63 0 0
#> 1 24.00 0 23 1 0
#> 11 24.00 0 42 0 1
#> 17 24.00 0 38 0 1
#> 151 24.00 0 42 0 0
#> 151.1 24.00 0 42 0 0
#> 138 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 102 24.00 0 49 0 0
#> 115 24.00 0 NA 1 0
#> 178.1 24.00 0 52 1 0
#> 48 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 19 24.00 0 57 0 1
#> 104.1 24.00 0 50 1 0
#> 191 24.00 0 60 0 1
#> 67 24.00 0 25 0 0
#> 31.1 24.00 0 36 0 1
#> 1.1 24.00 0 23 1 0
#> 44.1 24.00 0 56 0 0
#> 84 24.00 0 39 0 1
#> 9 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 38 24.00 0 31 1 0
#> 54.1 24.00 0 53 1 0
#> 95.1 24.00 0 68 0 1
#> 163 24.00 0 66 0 0
#> 83.1 24.00 0 6 0 0
#> 82 24.00 0 34 0 0
#> 3 24.00 0 31 1 0
#> 12.3 24.00 0 63 0 0
#> 7 24.00 0 37 1 0
#> 182.1 24.00 0 35 0 0
#> 65.1 24.00 0 57 1 0
#> 156 24.00 0 50 1 0
#> 118.1 24.00 0 44 1 0
#> 182.2 24.00 0 35 0 0
#> 109 24.00 0 48 0 0
#> 95.2 24.00 0 68 0 1
#> 118.2 24.00 0 44 1 0
#> 44.2 24.00 0 56 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.605 NA NA NA
#> 2 age, Cure model 0.00614 NA NA NA
#> 3 grade_ii, Cure model -0.102 NA NA NA
#> 4 grade_iii, Cure model 1.37 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00812 NA NA NA
#> 2 grade_ii, Survival model 1.12 NA NA NA
#> 3 grade_iii, Survival model 0.475 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.604500 0.006136 -0.101685 1.367743
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 252
#> Residual Deviance: 232.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.604500323 0.006135986 -0.101684777 1.367742805
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008119127 1.118191205 0.475185071
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.84981509 0.27272166 0.96599575 0.75611290 0.47549327 0.72605146
#> [7] 0.27272166 0.40798911 0.86786945 0.70585408 0.87696703 0.12161666
#> [13] 0.93963176 0.69582716 0.96599575 0.16298199 0.50802836 0.48645197
#> [19] 0.92185633 0.40798911 0.57234450 0.68568903 0.18649607 0.78493370
#> [25] 0.57234450 0.78493370 0.46445772 0.62452508 0.56164952 0.09637217
#> [31] 0.59349875 0.13544668 0.84981509 0.09637217 0.53997216 0.64512895
#> [37] 0.39613338 0.96599575 0.26190004 0.83153931 0.84072553 0.72605146
#> [43] 0.82224300 0.93963176 0.64512895 0.50802836 0.61423728 0.88605947
#> [49] 0.88605947 0.18649607 0.88605947 0.22902231 0.04614560 0.93077696
#> [55] 0.25122089 0.05919729 0.48645197 0.37299313 0.07265225 0.33861644
#> [61] 0.74603301 0.75611290 0.71592638 0.80353379 0.64512895 0.02583741
#> [67] 0.37299313 0.45343559 0.27272166 0.27272166 0.16298199 0.81293823
#> [73] 0.35017710 0.67552219 0.93963176 0.91289382 0.00330647 0.18649607
#> [79] 0.35017710 0.07265225 0.14902664 0.01290093 0.59349875 0.02583741
#> [85] 0.63479478 0.32704102 0.24044541 0.99144218 0.31557576 0.55092332
#> [91] 0.44248414 0.50802836 0.43112880 0.75611290 0.18649607 0.00000000
#> [97] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000
#>
#> $Time
#> 159 166 25 140 117 96 166.1 108 10 157 93 169 77
#> 10.55 19.98 6.32 12.68 17.46 14.54 19.98 18.29 10.53 15.10 10.33 22.41 7.27
#> 29 25.1 139 45 111 101 108.1 130 39 99 154 130.1 154.1
#> 15.45 6.32 21.49 17.42 17.45 9.97 18.29 16.47 15.59 21.19 12.63 16.47 12.63
#> 110 188 171 113 192 194 159.1 113.1 23 26 88 25.2 150
#> 17.56 16.16 16.57 22.86 16.44 22.40 10.55 22.86 16.92 15.77 18.37 6.32 20.33
#> 49 107 96.1 42 77.1 26.1 45.1 79 61 61.1 99.1 61.2 90
#> 12.19 11.18 14.54 12.43 7.27 15.77 17.42 16.23 10.12 10.12 21.19 10.12 20.94
#> 168 183 128 164 111.1 8 92 76 14 140.1 133 177 26.2
#> 23.72 9.24 20.35 23.60 17.45 18.43 22.92 19.22 12.89 12.68 14.65 12.53 15.77
#> 86 8.1 184 166.2 166.3 139.1 37 97 125 77.2 145 24 99.2
#> 23.81 18.43 17.77 19.98 19.98 21.49 12.52 19.14 15.65 7.27 10.07 23.89 21.19
#> 97.1 92.1 175 78 85 86.1 100 58 32 127 105 106 40
#> 19.14 22.92 21.91 23.88 16.44 23.81 16.07 19.34 20.90 3.53 19.75 16.67 18.00
#> 45.2 41 140.2 36 28 135 104 152 122 2 44 152.1 126
#> 17.42 18.02 12.68 21.19 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 95 185 21 165 141 12 103 80 122.1 126.1 20 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 196 200 94 116 126.2 21.1 172 53 137 27 137.1 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 176 64 75 165.1 12.1 27.1 182 20.1 118 22 54 12.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 11 17 151 151.1 138 65 102 178.1 48 31 19 104.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 67 31.1 1.1 44.1 84 9 83 38 54.1 95.1 163 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 3 12.3 7 182.1 65.1 156 118.1 182.2 109 95.2 118.2 44.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[91]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007865294 1.061666632 0.498004904
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.554372294 0.009640563 0.374219515
#> grade_iii, Cure model
#> 0.517328881
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 145 10.07 1 65 1 0
#> 154 12.63 1 20 1 0
#> 100 16.07 1 60 0 0
#> 100.1 16.07 1 60 0 0
#> 43 12.10 1 61 0 1
#> 24 23.89 1 38 0 0
#> 60 13.15 1 38 1 0
#> 166 19.98 1 48 0 0
#> 91 5.33 1 61 0 1
#> 124 9.73 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 108 18.29 1 39 0 1
#> 117 17.46 1 26 0 1
#> 76 19.22 1 54 0 1
#> 177 12.53 1 75 0 0
#> 175 21.91 1 43 0 0
#> 158 20.14 1 74 1 0
#> 37 12.52 1 57 1 0
#> 133 14.65 1 57 0 0
#> 110 17.56 1 65 0 1
#> 129 23.41 1 53 1 0
#> 145.1 10.07 1 65 1 0
#> 134 17.81 1 47 1 0
#> 13 14.34 1 54 0 1
#> 105 19.75 1 60 0 0
#> 113 22.86 1 34 0 0
#> 136 21.83 1 43 0 1
#> 68 20.62 1 44 0 0
#> 91.1 5.33 1 61 0 1
#> 154.1 12.63 1 20 1 0
#> 89 11.44 1 NA 0 0
#> 175.1 21.91 1 43 0 0
#> 50 10.02 1 NA 1 0
#> 124.1 9.73 1 NA 1 0
#> 145.2 10.07 1 65 1 0
#> 40 18.00 1 28 1 0
#> 192 16.44 1 31 1 0
#> 164 23.60 1 76 0 1
#> 92 22.92 1 47 0 1
#> 111 17.45 1 47 0 1
#> 180 14.82 1 37 0 0
#> 96 14.54 1 33 0 1
#> 90 20.94 1 50 0 1
#> 49 12.19 1 48 1 0
#> 6 15.64 1 39 0 0
#> 106 16.67 1 49 1 0
#> 140 12.68 1 59 1 0
#> 149 8.37 1 33 1 0
#> 124.2 9.73 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 158.1 20.14 1 74 1 0
#> 154.2 12.63 1 20 1 0
#> 110.1 17.56 1 65 0 1
#> 56 12.21 1 60 0 0
#> 90.1 20.94 1 50 0 1
#> 140.1 12.68 1 59 1 0
#> 164.1 23.60 1 76 0 1
#> 168 23.72 1 70 0 0
#> 154.3 12.63 1 20 1 0
#> 42.1 12.43 1 49 0 1
#> 199 19.81 1 NA 0 1
#> 93 10.33 1 52 0 1
#> 96.1 14.54 1 33 0 1
#> 197 21.60 1 69 1 0
#> 68.1 20.62 1 44 0 0
#> 127 3.53 1 62 0 1
#> 136.1 21.83 1 43 0 1
#> 63 22.77 1 31 1 0
#> 78 23.88 1 43 0 0
#> 59 10.16 1 NA 1 0
#> 96.2 14.54 1 33 0 1
#> 140.2 12.68 1 59 1 0
#> 96.3 14.54 1 33 0 1
#> 199.1 19.81 1 NA 0 1
#> 117.1 17.46 1 26 0 1
#> 145.3 10.07 1 65 1 0
#> 180.1 14.82 1 37 0 0
#> 96.4 14.54 1 33 0 1
#> 101 9.97 1 10 0 1
#> 111.1 17.45 1 47 0 1
#> 79 16.23 1 54 1 0
#> 108.1 18.29 1 39 0 1
#> 58 19.34 1 39 0 0
#> 169 22.41 1 46 0 0
#> 26 15.77 1 49 0 1
#> 134.1 17.81 1 47 1 0
#> 42.2 12.43 1 49 0 1
#> 14 12.89 1 21 0 0
#> 168.1 23.72 1 70 0 0
#> 150 20.33 1 48 0 0
#> 60.1 13.15 1 38 1 0
#> 15 22.68 1 48 0 0
#> 86 23.81 1 58 0 1
#> 96.5 14.54 1 33 0 1
#> 69 23.23 1 25 0 1
#> 164.2 23.60 1 76 0 1
#> 10 10.53 1 34 0 0
#> 58.1 19.34 1 39 0 0
#> 195 11.76 1 NA 1 0
#> 106.1 16.67 1 49 1 0
#> 96.6 14.54 1 33 0 1
#> 4 17.64 1 NA 0 1
#> 107 11.18 1 54 1 0
#> 175.2 21.91 1 43 0 0
#> 69.1 23.23 1 25 0 1
#> 26.1 15.77 1 49 0 1
#> 24.1 23.89 1 38 0 0
#> 194 22.40 1 38 0 1
#> 125 15.65 1 67 1 0
#> 43.1 12.10 1 61 0 1
#> 187 9.92 1 39 1 0
#> 85 16.44 1 36 0 0
#> 109 24.00 0 48 0 0
#> 31 24.00 0 36 0 1
#> 7 24.00 0 37 1 0
#> 71 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 156 24.00 0 50 1 0
#> 135 24.00 0 58 1 0
#> 115 24.00 0 NA 1 0
#> 94 24.00 0 51 0 1
#> 2 24.00 0 9 0 0
#> 9 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 132 24.00 0 55 0 0
#> 142 24.00 0 53 0 0
#> 122 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 115.1 24.00 0 NA 1 0
#> 193 24.00 0 45 0 1
#> 131 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 75 24.00 0 21 1 0
#> 196 24.00 0 19 0 0
#> 193.1 24.00 0 45 0 1
#> 48 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 48.1 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 148 24.00 0 61 1 0
#> 82 24.00 0 34 0 0
#> 104 24.00 0 50 1 0
#> 94.1 24.00 0 51 0 1
#> 112 24.00 0 61 0 0
#> 1 24.00 0 23 1 0
#> 12 24.00 0 63 0 0
#> 163 24.00 0 66 0 0
#> 182.1 24.00 0 35 0 0
#> 193.2 24.00 0 45 0 1
#> 19 24.00 0 57 0 1
#> 67 24.00 0 25 0 0
#> 191 24.00 0 60 0 1
#> 185 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 31.1 24.00 0 36 0 1
#> 74 24.00 0 43 0 1
#> 46 24.00 0 71 0 0
#> 182.2 24.00 0 35 0 0
#> 102 24.00 0 49 0 0
#> 35 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 120.1 24.00 0 68 0 1
#> 102.1 24.00 0 49 0 0
#> 193.3 24.00 0 45 0 1
#> 178 24.00 0 52 1 0
#> 131.1 24.00 0 66 0 0
#> 1.1 24.00 0 23 1 0
#> 198 24.00 0 66 0 1
#> 74.1 24.00 0 43 0 1
#> 176 24.00 0 43 0 1
#> 191.1 24.00 0 60 0 1
#> 1.2 24.00 0 23 1 0
#> 28 24.00 0 67 1 0
#> 64 24.00 0 43 0 0
#> 17.1 24.00 0 38 0 1
#> 143.1 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 191.2 24.00 0 60 0 1
#> 9.1 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 65 24.00 0 57 1 0
#> 126 24.00 0 48 0 0
#> 135.1 24.00 0 58 1 0
#> 112.1 24.00 0 61 0 0
#> 21 24.00 0 47 0 0
#> 144 24.00 0 28 0 1
#> 84 24.00 0 39 0 1
#> 53 24.00 0 32 0 1
#> 185.1 24.00 0 44 1 0
#> 17.2 24.00 0 38 0 1
#> 38 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 141 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 176.1 24.00 0 43 0 1
#> 54 24.00 0 53 1 0
#> 173 24.00 0 19 0 1
#> 21.1 24.00 0 47 0 0
#> 31.2 24.00 0 36 0 1
#> 115.2 24.00 0 NA 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.554 NA NA NA
#> 2 age, Cure model 0.00964 NA NA NA
#> 3 grade_ii, Cure model 0.374 NA NA NA
#> 4 grade_iii, Cure model 0.517 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00787 NA NA NA
#> 2 grade_ii, Survival model 1.06 NA NA NA
#> 3 grade_iii, Survival model 0.498 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.554372 0.009641 0.374220 0.517329
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.1
#> Residual Deviance: 253.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.554372294 0.009640563 0.374219515 0.517328881
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007865294 1.061666632 0.498004904
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.923028774 0.793725631 0.584817951 0.584817951 0.882843082 0.005519037
#> [7] 0.741001016 0.368654119 0.977121682 0.842420069 0.424124099 0.497367150
#> [13] 0.412899305 0.826023964 0.214051162 0.347242684 0.834256117 0.660010746
#> [19] 0.477066299 0.109730070 0.923028774 0.456776932 0.731774952 0.379621634
#> [25] 0.157192783 0.247562653 0.313917000 0.977121682 0.793725631 0.214051162
#> [31] 0.923028774 0.446035702 0.556534221 0.071947138 0.145426785 0.517389372
#> [37] 0.641212410 0.669527130 0.292346179 0.874754820 0.631813436 0.537306161
#> [43] 0.767818735 0.969473072 0.281262476 0.347242684 0.793725631 0.477066299
#> [49] 0.866592442 0.292346179 0.767818735 0.071947138 0.045631037 0.793725631
#> [55] 0.842420069 0.914998038 0.669527130 0.270081766 0.313917000 0.992354666
#> [61] 0.247562653 0.169169461 0.021254165 0.669527130 0.767818735 0.669527130
#> [67] 0.497367150 0.923028774 0.641212410 0.669527130 0.953955357 0.517389372
#> [73] 0.575429755 0.424124099 0.390709674 0.191369485 0.603669530 0.456776932
#> [79] 0.842420069 0.758833377 0.045631037 0.335930769 0.741001016 0.180161885
#> [85] 0.033510382 0.669527130 0.122605680 0.071947138 0.906960737 0.390709674
#> [91] 0.537306161 0.669527130 0.898940114 0.214051162 0.122605680 0.603669530
#> [97] 0.005519037 0.202780094 0.622451255 0.882843082 0.961749499 0.556534221
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 145 154 100 100.1 43 24 60 166 91 42 108 117 76
#> 10.07 12.63 16.07 16.07 12.10 23.89 13.15 19.98 5.33 12.43 18.29 17.46 19.22
#> 177 175 158 37 133 110 129 145.1 134 13 105 113 136
#> 12.53 21.91 20.14 12.52 14.65 17.56 23.41 10.07 17.81 14.34 19.75 22.86 21.83
#> 68 91.1 154.1 175.1 145.2 40 192 164 92 111 180 96 90
#> 20.62 5.33 12.63 21.91 10.07 18.00 16.44 23.60 22.92 17.45 14.82 14.54 20.94
#> 49 6 106 140 149 99 158.1 154.2 110.1 56 90.1 140.1 164.1
#> 12.19 15.64 16.67 12.68 8.37 21.19 20.14 12.63 17.56 12.21 20.94 12.68 23.60
#> 168 154.3 42.1 93 96.1 197 68.1 127 136.1 63 78 96.2 140.2
#> 23.72 12.63 12.43 10.33 14.54 21.60 20.62 3.53 21.83 22.77 23.88 14.54 12.68
#> 96.3 117.1 145.3 180.1 96.4 101 111.1 79 108.1 58 169 26 134.1
#> 14.54 17.46 10.07 14.82 14.54 9.97 17.45 16.23 18.29 19.34 22.41 15.77 17.81
#> 42.2 14 168.1 150 60.1 15 86 96.5 69 164.2 10 58.1 106.1
#> 12.43 12.89 23.72 20.33 13.15 22.68 23.81 14.54 23.23 23.60 10.53 19.34 16.67
#> 96.6 107 175.2 69.1 26.1 24.1 194 125 43.1 187 85 109 31
#> 14.54 11.18 21.91 23.23 15.77 23.89 22.40 15.65 12.10 9.92 16.44 24.00 24.00
#> 7 71 172 156 135 94 2 9 182 132 142 122 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 131 87 75 196 193.1 48 143 48.1 11 148 82 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 112 1 12 163 182.1 193.2 19 67 191 185 120 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 46 182.2 102 35 17 120.1 102.1 193.3 178 131.1 1.1 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 176 191.1 1.2 28 64 17.1 143.1 200 191.2 9.1 65 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 112.1 21 144 84 53 185.1 17.2 38 172.1 141 137 176.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 173 21.1 31.2
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[92]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01017967 0.31270495 0.02469452
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.8534842 0.0308903 0.5823427
#> grade_iii, Cure model
#> 1.2763854
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 60 13.15 1 38 1 0
#> 175 21.91 1 43 0 0
#> 190 20.81 1 42 1 0
#> 171 16.57 1 41 0 1
#> 197 21.60 1 69 1 0
#> 79 16.23 1 54 1 0
#> 188 16.16 1 46 0 1
#> 153 21.33 1 55 1 0
#> 32 20.90 1 37 1 0
#> 37 12.52 1 57 1 0
#> 68 20.62 1 44 0 0
#> 49 12.19 1 48 1 0
#> 108 18.29 1 39 0 1
#> 50 10.02 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 49.1 12.19 1 48 1 0
#> 192 16.44 1 31 1 0
#> 195 11.76 1 NA 1 0
#> 93 10.33 1 52 0 1
#> 167.1 15.55 1 56 1 0
#> 164 23.60 1 76 0 1
#> 13 14.34 1 54 0 1
#> 43 12.10 1 61 0 1
#> 4 17.64 1 NA 0 1
#> 69 23.23 1 25 0 1
#> 111 17.45 1 47 0 1
#> 6 15.64 1 39 0 0
#> 197.1 21.60 1 69 1 0
#> 70 7.38 1 30 1 0
#> 86 23.81 1 58 0 1
#> 39 15.59 1 37 0 1
#> 85 16.44 1 36 0 0
#> 57 14.46 1 45 0 1
#> 37.1 12.52 1 57 1 0
#> 136 21.83 1 43 0 1
#> 30 17.43 1 78 0 0
#> 16 8.71 1 71 0 1
#> 51 18.23 1 83 0 1
#> 88 18.37 1 47 0 0
#> 123 13.00 1 44 1 0
#> 23 16.92 1 61 0 0
#> 184 17.77 1 38 0 0
#> 107 11.18 1 54 1 0
#> 56 12.21 1 60 0 0
#> 96 14.54 1 33 0 1
#> 88.1 18.37 1 47 0 0
#> 153.1 21.33 1 55 1 0
#> 110 17.56 1 65 0 1
#> 155 13.08 1 26 0 0
#> 42 12.43 1 49 0 1
#> 181 16.46 1 45 0 1
#> 96.1 14.54 1 33 0 1
#> 197.2 21.60 1 69 1 0
#> 42.1 12.43 1 49 0 1
#> 77 7.27 1 67 0 1
#> 93.1 10.33 1 52 0 1
#> 78 23.88 1 43 0 0
#> 97 19.14 1 65 0 1
#> 140 12.68 1 59 1 0
#> 91 5.33 1 61 0 1
#> 14 12.89 1 21 0 0
#> 55 19.34 1 69 0 1
#> 180 14.82 1 37 0 0
#> 6.1 15.64 1 39 0 0
#> 56.1 12.21 1 60 0 0
#> 180.1 14.82 1 37 0 0
#> 49.2 12.19 1 48 1 0
#> 50.1 10.02 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 88.2 18.37 1 47 0 0
#> 123.1 13.00 1 44 1 0
#> 134 17.81 1 47 1 0
#> 55.1 19.34 1 69 0 1
#> 69.1 23.23 1 25 0 1
#> 92 22.92 1 47 0 1
#> 106 16.67 1 49 1 0
#> 111.1 17.45 1 47 0 1
#> 61 10.12 1 36 0 1
#> 50.2 10.02 1 NA 1 0
#> 140.1 12.68 1 59 1 0
#> 4.1 17.64 1 NA 0 1
#> 164.1 23.60 1 76 0 1
#> 136.1 21.83 1 43 0 1
#> 36 21.19 1 48 0 1
#> 189 10.51 1 NA 1 0
#> 49.3 12.19 1 48 1 0
#> 180.2 14.82 1 37 0 0
#> 153.2 21.33 1 55 1 0
#> 192.1 16.44 1 31 1 0
#> 52 10.42 1 52 0 1
#> 114 13.68 1 NA 0 0
#> 89 11.44 1 NA 0 0
#> 134.1 17.81 1 47 1 0
#> 25 6.32 1 34 1 0
#> 197.3 21.60 1 69 1 0
#> 89.1 11.44 1 NA 0 0
#> 32.1 20.90 1 37 1 0
#> 81 14.06 1 34 0 0
#> 26 15.77 1 49 0 1
#> 24 23.89 1 38 0 0
#> 29 15.45 1 68 1 0
#> 39.1 15.59 1 37 0 1
#> 56.2 12.21 1 60 0 0
#> 30.1 17.43 1 78 0 0
#> 89.2 11.44 1 NA 0 0
#> 23.1 16.92 1 61 0 0
#> 199 19.81 1 NA 0 1
#> 86.1 23.81 1 58 0 1
#> 199.1 19.81 1 NA 0 1
#> 96.2 14.54 1 33 0 1
#> 6.2 15.64 1 39 0 0
#> 10 10.53 1 34 0 0
#> 17 24.00 0 38 0 1
#> 174 24.00 0 49 1 0
#> 34 24.00 0 36 0 0
#> 84 24.00 0 39 0 1
#> 132 24.00 0 55 0 0
#> 84.1 24.00 0 39 0 1
#> 102 24.00 0 49 0 0
#> 172 24.00 0 41 0 0
#> 161 24.00 0 45 0 0
#> 163 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 142 24.00 0 53 0 0
#> 21 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 196 24.00 0 19 0 0
#> 22 24.00 0 52 1 0
#> 143 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 103 24.00 0 56 1 0
#> 44 24.00 0 56 0 0
#> 46 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 87.1 24.00 0 27 0 0
#> 116 24.00 0 58 0 1
#> 35 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 144 24.00 0 28 0 1
#> 112 24.00 0 61 0 0
#> 119 24.00 0 17 0 0
#> 115 24.00 0 NA 1 0
#> 196.1 24.00 0 19 0 0
#> 11 24.00 0 42 0 1
#> 35.1 24.00 0 51 0 0
#> 22.1 24.00 0 52 1 0
#> 138 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 3 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 48.1 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 67 24.00 0 25 0 0
#> 151 24.00 0 42 0 0
#> 75 24.00 0 21 1 0
#> 84.2 24.00 0 39 0 1
#> 132.1 24.00 0 55 0 0
#> 109.1 24.00 0 48 0 0
#> 182 24.00 0 35 0 0
#> 118 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 112.2 24.00 0 61 0 0
#> 122 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 31.1 24.00 0 36 0 1
#> 87.2 24.00 0 27 0 0
#> 178 24.00 0 52 1 0
#> 48.2 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 44.1 24.00 0 56 0 0
#> 118.1 24.00 0 44 1 0
#> 141.1 24.00 0 44 1 0
#> 67.1 24.00 0 25 0 0
#> 161.1 24.00 0 45 0 0
#> 28 24.00 0 67 1 0
#> 121 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 116.1 24.00 0 58 0 1
#> 94.1 24.00 0 51 0 1
#> 165.1 24.00 0 47 0 0
#> 142.1 24.00 0 53 0 0
#> 141.2 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 94.2 24.00 0 51 0 1
#> 186.1 24.00 0 45 1 0
#> 1.1 24.00 0 23 1 0
#> 67.2 24.00 0 25 0 0
#> 148 24.00 0 61 1 0
#> 44.2 24.00 0 56 0 0
#> 109.2 24.00 0 48 0 0
#> 186.2 24.00 0 45 1 0
#> 94.3 24.00 0 51 0 1
#> 67.3 24.00 0 25 0 0
#> 47 24.00 0 38 0 1
#> 173 24.00 0 19 0 1
#> 1.2 24.00 0 23 1 0
#> 138.1 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.85 NA NA NA
#> 2 age, Cure model 0.0309 NA NA NA
#> 3 grade_ii, Cure model 0.582 NA NA NA
#> 4 grade_iii, Cure model 1.28 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0102 NA NA NA
#> 2 grade_ii, Survival model 0.313 NA NA NA
#> 3 grade_iii, Survival model 0.0247 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.85348 0.03089 0.58234 1.27639
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.6
#> Residual Deviance: 235.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.8534842 0.0308903 0.5823427 1.2763854
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01017967 0.31270495 0.02469452
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.584240313 0.032406593 0.113663770 0.299565310 0.049444673 0.352114969
#> [7] 0.362947569 0.072884227 0.099612750 0.672654509 0.120971722 0.764012608
#> [13] 0.176378206 0.440940254 0.764012608 0.320803690 0.872135643 0.440940254
#> [19] 0.010107577 0.559259432 0.817017725 0.018181940 0.230210775 0.384969402
#> [25] 0.049444673 0.942572740 0.004483830 0.418152193 0.320803690 0.546921114
#> [31] 0.672654509 0.038003849 0.249075400 0.928318758 0.185073621 0.151913191
#> [37] 0.609401192 0.268757210 0.211697346 0.830706404 0.724352476 0.511013361
#> [43] 0.151913191 0.072884227 0.220862667 0.596789914 0.698322838 0.310120549
#> [49] 0.511013361 0.049444673 0.698322838 0.956825144 0.872135643 0.002107698
#> [55] 0.143805200 0.647214152 0.985542970 0.634492860 0.128442709 0.475768718
#> [61] 0.384969402 0.724352476 0.475768718 0.764012608 0.914173904 0.151913191
#> [67] 0.609401192 0.194003892 0.128442709 0.018181940 0.027133580 0.289129510
#> [73] 0.230210775 0.900045277 0.647214152 0.010107577 0.038003849 0.092387572
#> [79] 0.764012608 0.475768718 0.072884227 0.320803690 0.858244982 0.194003892
#> [85] 0.971180568 0.049444673 0.099612750 0.571709951 0.373897266 0.000483499
#> [91] 0.463998924 0.418152193 0.724352476 0.249075400 0.268757210 0.004483830
#> [97] 0.511013361 0.384969402 0.844442848 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 60 175 190 171 197 79 188 153 32 37 68 49 108
#> 13.15 21.91 20.81 16.57 21.60 16.23 16.16 21.33 20.90 12.52 20.62 12.19 18.29
#> 167 49.1 192 93 167.1 164 13 43 69 111 6 197.1 70
#> 15.55 12.19 16.44 10.33 15.55 23.60 14.34 12.10 23.23 17.45 15.64 21.60 7.38
#> 86 39 85 57 37.1 136 30 16 51 88 123 23 184
#> 23.81 15.59 16.44 14.46 12.52 21.83 17.43 8.71 18.23 18.37 13.00 16.92 17.77
#> 107 56 96 88.1 153.1 110 155 42 181 96.1 197.2 42.1 77
#> 11.18 12.21 14.54 18.37 21.33 17.56 13.08 12.43 16.46 14.54 21.60 12.43 7.27
#> 93.1 78 97 140 91 14 55 180 6.1 56.1 180.1 49.2 101
#> 10.33 23.88 19.14 12.68 5.33 12.89 19.34 14.82 15.64 12.21 14.82 12.19 9.97
#> 88.2 123.1 134 55.1 69.1 92 106 111.1 61 140.1 164.1 136.1 36
#> 18.37 13.00 17.81 19.34 23.23 22.92 16.67 17.45 10.12 12.68 23.60 21.83 21.19
#> 49.3 180.2 153.2 192.1 52 134.1 25 197.3 32.1 81 26 24 29
#> 12.19 14.82 21.33 16.44 10.42 17.81 6.32 21.60 20.90 14.06 15.77 23.89 15.45
#> 39.1 56.2 30.1 23.1 86.1 96.2 6.2 10 17 174 34 84 132
#> 15.59 12.21 17.43 16.92 23.81 14.54 15.64 10.53 24.00 24.00 24.00 24.00 24.00
#> 84.1 102 172 161 163 165 142 21 48 1 196 22 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 103 44 46 31 87.1 116 35 193 144 112 119 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 35.1 22.1 138 2 3 48.1 185 141 109 67 151 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84.2 132.1 109.1 182 118 112.1 112.2 122 94 31.1 87.2 178 48.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 44.1 118.1 141.1 67.1 161.1 28 121 186 116.1 94.1 165.1 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.2 98 94.2 186.1 1.1 67.2 148 44.2 109.2 186.2 94.3 67.3 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 1.2 138.1
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[93]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004859979 0.618639712 0.056480176
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.162304306 -0.003240534 0.446069528
#> grade_iii, Cure model
#> 1.150279315
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 79 16.23 1 54 1 0
#> 175 21.91 1 43 0 0
#> 194 22.40 1 38 0 1
#> 180 14.82 1 37 0 0
#> 145 10.07 1 65 1 0
#> 149 8.37 1 33 1 0
#> 13 14.34 1 54 0 1
#> 140 12.68 1 59 1 0
#> 129 23.41 1 53 1 0
#> 180.1 14.82 1 37 0 0
#> 60 13.15 1 38 1 0
#> 187 9.92 1 39 1 0
#> 36 21.19 1 48 0 1
#> 149.1 8.37 1 33 1 0
#> 92 22.92 1 47 0 1
#> 108 18.29 1 39 0 1
#> 77 7.27 1 67 0 1
#> 49 12.19 1 48 1 0
#> 14 12.89 1 21 0 0
#> 192 16.44 1 31 1 0
#> 91 5.33 1 61 0 1
#> 170 19.54 1 43 0 1
#> 145.1 10.07 1 65 1 0
#> 18 15.21 1 49 1 0
#> 68 20.62 1 44 0 0
#> 166 19.98 1 48 0 0
#> 5 16.43 1 51 0 1
#> 101 9.97 1 10 0 1
#> 180.2 14.82 1 37 0 0
#> 114 13.68 1 NA 0 0
#> 195 11.76 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 107 11.18 1 54 1 0
#> 108.1 18.29 1 39 0 1
#> 134 17.81 1 47 1 0
#> 181 16.46 1 45 0 1
#> 124 9.73 1 NA 1 0
#> 14.1 12.89 1 21 0 0
#> 188 16.16 1 46 0 1
#> 49.1 12.19 1 48 1 0
#> 97 19.14 1 65 0 1
#> 127 3.53 1 62 0 1
#> 181.1 16.46 1 45 0 1
#> 60.1 13.15 1 38 1 0
#> 100 16.07 1 60 0 0
#> 96 14.54 1 33 0 1
#> 81 14.06 1 34 0 0
#> 36.1 21.19 1 48 0 1
#> 4 17.64 1 NA 0 1
#> 96.1 14.54 1 33 0 1
#> 106 16.67 1 49 1 0
#> 32 20.90 1 37 1 0
#> 97.1 19.14 1 65 0 1
#> 16 8.71 1 71 0 1
#> 100.1 16.07 1 60 0 0
#> 52 10.42 1 52 0 1
#> 192.1 16.44 1 31 1 0
#> 123 13.00 1 44 1 0
#> 58 19.34 1 39 0 0
#> 40 18.00 1 28 1 0
#> 91.1 5.33 1 61 0 1
#> 69 23.23 1 25 0 1
#> 85 16.44 1 36 0 0
#> 194.1 22.40 1 38 0 1
#> 128 20.35 1 35 0 1
#> 180.3 14.82 1 37 0 0
#> 188.1 16.16 1 46 0 1
#> 70 7.38 1 30 1 0
#> 6 15.64 1 39 0 0
#> 155 13.08 1 26 0 0
#> 194.2 22.40 1 38 0 1
#> 149.2 8.37 1 33 1 0
#> 5.1 16.43 1 51 0 1
#> 85.1 16.44 1 36 0 0
#> 199 19.81 1 NA 0 1
#> 130 16.47 1 53 0 1
#> 189 10.51 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 91.2 5.33 1 61 0 1
#> 188.2 16.16 1 46 0 1
#> 154 12.63 1 20 1 0
#> 86 23.81 1 58 0 1
#> 78 23.88 1 43 0 0
#> 32.1 20.90 1 37 1 0
#> 129.1 23.41 1 53 1 0
#> 107.1 11.18 1 54 1 0
#> 128.1 20.35 1 35 0 1
#> 52.1 10.42 1 52 0 1
#> 179 18.63 1 42 0 0
#> 56 12.21 1 60 0 0
#> 29 15.45 1 68 1 0
#> 5.2 16.43 1 51 0 1
#> 15 22.68 1 48 0 0
#> 97.2 19.14 1 65 0 1
#> 85.2 16.44 1 36 0 0
#> 76 19.22 1 54 0 1
#> 81.1 14.06 1 34 0 0
#> 187.1 9.92 1 39 1 0
#> 114.1 13.68 1 NA 0 0
#> 99 21.19 1 38 0 1
#> 99.1 21.19 1 38 0 1
#> 108.2 18.29 1 39 0 1
#> 110 17.56 1 65 0 1
#> 168 23.72 1 70 0 0
#> 170.1 19.54 1 43 0 1
#> 100.2 16.07 1 60 0 0
#> 76.1 19.22 1 54 0 1
#> 88 18.37 1 47 0 0
#> 25 6.32 1 34 1 0
#> 169 22.41 1 46 0 0
#> 15.1 22.68 1 48 0 0
#> 189.1 10.51 1 NA 1 0
#> 3 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 182 24.00 0 35 0 0
#> 62 24.00 0 71 0 0
#> 54 24.00 0 53 1 0
#> 144 24.00 0 28 0 1
#> 74 24.00 0 43 0 1
#> 115 24.00 0 NA 1 0
#> 34 24.00 0 36 0 0
#> 64 24.00 0 43 0 0
#> 151 24.00 0 42 0 0
#> 7 24.00 0 37 1 0
#> 162 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 64.1 24.00 0 43 0 0
#> 71 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 74.1 24.00 0 43 0 1
#> 193 24.00 0 45 0 1
#> 173 24.00 0 19 0 1
#> 156 24.00 0 50 1 0
#> 173.1 24.00 0 19 0 1
#> 94 24.00 0 51 0 1
#> 115.1 24.00 0 NA 1 0
#> 193.1 24.00 0 45 0 1
#> 54.1 24.00 0 53 1 0
#> 75 24.00 0 21 1 0
#> 163 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 161 24.00 0 45 0 0
#> 142 24.00 0 53 0 0
#> 146 24.00 0 63 1 0
#> 20 24.00 0 46 1 0
#> 144.1 24.00 0 28 0 1
#> 132 24.00 0 55 0 0
#> 12 24.00 0 63 0 0
#> 1 24.00 0 23 1 0
#> 46 24.00 0 71 0 0
#> 33 24.00 0 53 0 0
#> 143.1 24.00 0 51 0 0
#> 138.1 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 33.1 24.00 0 53 0 0
#> 74.2 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 80 24.00 0 41 0 0
#> 48 24.00 0 31 1 0
#> 64.2 24.00 0 43 0 0
#> 102 24.00 0 49 0 0
#> 116 24.00 0 58 0 1
#> 152 24.00 0 36 0 1
#> 162.1 24.00 0 51 0 0
#> 162.2 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 138.2 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 12.1 24.00 0 63 0 0
#> 138.3 24.00 0 44 1 0
#> 64.3 24.00 0 43 0 0
#> 48.1 24.00 0 31 1 0
#> 64.4 24.00 0 43 0 0
#> 109 24.00 0 48 0 0
#> 191 24.00 0 60 0 1
#> 72 24.00 0 40 0 1
#> 98 24.00 0 34 1 0
#> 54.2 24.00 0 53 1 0
#> 144.2 24.00 0 28 0 1
#> 198 24.00 0 66 0 1
#> 132.1 24.00 0 55 0 0
#> 102.1 24.00 0 49 0 0
#> 131 24.00 0 66 0 0
#> 152.1 24.00 0 36 0 1
#> 82 24.00 0 34 0 0
#> 74.3 24.00 0 43 0 1
#> 22 24.00 0 52 1 0
#> 138.4 24.00 0 44 1 0
#> 132.2 24.00 0 55 0 0
#> 160 24.00 0 31 1 0
#> 138.5 24.00 0 44 1 0
#> 80.1 24.00 0 41 0 0
#> 200.1 24.00 0 64 0 0
#> 31 24.00 0 36 0 1
#> 7.1 24.00 0 37 1 0
#> 62.1 24.00 0 71 0 0
#> 104 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.162 NA NA NA
#> 2 age, Cure model -0.00324 NA NA NA
#> 3 grade_ii, Cure model 0.446 NA NA NA
#> 4 grade_iii, Cure model 1.15 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00486 NA NA NA
#> 2 grade_ii, Survival model 0.619 NA NA NA
#> 3 grade_iii, Survival model 0.0565 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.162304 -0.003241 0.446070 1.150279
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 251.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.162304306 -0.003240534 0.446069528 1.150279315
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004859979 0.618639712 0.056480176
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.514292640 0.119569067 0.093106097 0.613296530 0.850134529 0.907300962
#> [7] 0.672660774 0.762630357 0.033150994 0.613296530 0.702961394 0.878871790
#> [13] 0.129281832 0.907300962 0.057371345 0.327744459 0.944375317 0.792267336
#> [19] 0.742806237 0.437685948 0.962959382 0.220641107 0.850134529 0.603325864
#> [25] 0.183409019 0.211142702 0.485011323 0.869257813 0.613296530 0.377758108
#> [31] 0.811660767 0.327744459 0.367792302 0.417788953 0.742806237 0.524162693
#> [37] 0.792267336 0.268349260 0.990659964 0.417788953 0.702961394 0.553469108
#> [43] 0.652628611 0.682780821 0.129281832 0.652628611 0.397838221 0.165390857
#> [49] 0.268349260 0.897774202 0.553469108 0.830857959 0.437685948 0.732853109
#> [55] 0.239454001 0.357695943 0.962959382 0.048733141 0.437685948 0.093106097
#> [61] 0.192741566 0.613296530 0.524162693 0.935078962 0.583173630 0.722832070
#> [67] 0.093106097 0.907300962 0.485011323 0.437685948 0.407791356 0.307442598
#> [73] 0.962959382 0.524162693 0.772556569 0.011576763 0.003375625 0.165390857
#> [79] 0.033150994 0.811660767 0.192741566 0.830857959 0.297372565 0.782396252
#> [85] 0.593278320 0.485011323 0.066222254 0.268349260 0.437685948 0.249119783
#> [91] 0.682780821 0.878871790 0.129281832 0.129281832 0.327744459 0.387768459
#> [97] 0.021547683 0.220641107 0.553469108 0.249119783 0.317560387 0.953693317
#> [103] 0.083665644 0.066222254 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 79 175 194 180 145 149 13 140 129 180.1 60 187 36
#> 16.23 21.91 22.40 14.82 10.07 8.37 14.34 12.68 23.41 14.82 13.15 9.92 21.19
#> 149.1 92 108 77 49 14 192 91 170 145.1 18 68 166
#> 8.37 22.92 18.29 7.27 12.19 12.89 16.44 5.33 19.54 10.07 15.21 20.62 19.98
#> 5 101 180.2 184 107 108.1 134 181 14.1 188 49.1 97 127
#> 16.43 9.97 14.82 17.77 11.18 18.29 17.81 16.46 12.89 16.16 12.19 19.14 3.53
#> 181.1 60.1 100 96 81 36.1 96.1 106 32 97.1 16 100.1 52
#> 16.46 13.15 16.07 14.54 14.06 21.19 14.54 16.67 20.90 19.14 8.71 16.07 10.42
#> 192.1 123 58 40 91.1 69 85 194.1 128 180.3 188.1 70 6
#> 16.44 13.00 19.34 18.00 5.33 23.23 16.44 22.40 20.35 14.82 16.16 7.38 15.64
#> 155 194.2 149.2 5.1 85.1 130 8 91.2 188.2 154 86 78 32.1
#> 13.08 22.40 8.37 16.43 16.44 16.47 18.43 5.33 16.16 12.63 23.81 23.88 20.90
#> 129.1 107.1 128.1 52.1 179 56 29 5.2 15 97.2 85.2 76 81.1
#> 23.41 11.18 20.35 10.42 18.63 12.21 15.45 16.43 22.68 19.14 16.44 19.22 14.06
#> 187.1 99 99.1 108.2 110 168 170.1 100.2 76.1 88 25 169 15.1
#> 9.92 21.19 21.19 18.29 17.56 23.72 19.54 16.07 19.22 18.37 6.32 22.41 22.68
#> 3 178 87 182 62 54 144 74 34 64 151 7 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 64.1 71 143 74.1 193 173 156 173.1 94 193.1 54.1 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 138 67 161 142 146 20 144.1 132 12 1 46 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.1 138.1 200 33.1 74.2 27 80 48 64.2 102 116 152 162.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.2 2 138.2 122 172 12.1 138.3 64.3 48.1 64.4 109 191 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 54.2 144.2 198 132.1 102.1 131 152.1 82 74.3 22 138.4 132.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 138.5 80.1 200.1 31 7.1 62.1 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[94]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008195561 0.293063738 0.003025000
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.16481067 0.01634918 0.53159015
#> grade_iii, Cure model
#> 0.99037400
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 51 18.23 1 83 0 1
#> 14 12.89 1 21 0 0
#> 96 14.54 1 33 0 1
#> 89 11.44 1 NA 0 0
#> 51.1 18.23 1 83 0 1
#> 101 9.97 1 10 0 1
#> 51.2 18.23 1 83 0 1
#> 79 16.23 1 54 1 0
#> 105 19.75 1 60 0 0
#> 89.1 11.44 1 NA 0 0
#> 190 20.81 1 42 1 0
#> 55 19.34 1 69 0 1
#> 187 9.92 1 39 1 0
#> 76 19.22 1 54 0 1
#> 36 21.19 1 48 0 1
#> 37 12.52 1 57 1 0
#> 125 15.65 1 67 1 0
#> 41 18.02 1 40 1 0
#> 45 17.42 1 54 0 1
#> 192 16.44 1 31 1 0
#> 154 12.63 1 20 1 0
#> 183 9.24 1 67 1 0
#> 79.1 16.23 1 54 1 0
#> 37.1 12.52 1 57 1 0
#> 130 16.47 1 53 0 1
#> 134 17.81 1 47 1 0
#> 93 10.33 1 52 0 1
#> 25 6.32 1 34 1 0
#> 56 12.21 1 60 0 0
#> 128 20.35 1 35 0 1
#> 23 16.92 1 61 0 0
#> 134.1 17.81 1 47 1 0
#> 101.1 9.97 1 10 0 1
#> 158 20.14 1 74 1 0
#> 59 10.16 1 NA 1 0
#> 183.1 9.24 1 67 1 0
#> 158.1 20.14 1 74 1 0
#> 117 17.46 1 26 0 1
#> 188 16.16 1 46 0 1
#> 50 10.02 1 NA 1 0
#> 154.1 12.63 1 20 1 0
#> 18 15.21 1 49 1 0
#> 88 18.37 1 47 0 0
#> 51.3 18.23 1 83 0 1
#> 85 16.44 1 36 0 0
#> 59.1 10.16 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 155 13.08 1 26 0 0
#> 51.4 18.23 1 83 0 1
#> 136 21.83 1 43 0 1
#> 81 14.06 1 34 0 0
#> 171 16.57 1 41 0 1
#> 68 20.62 1 44 0 0
#> 134.2 17.81 1 47 1 0
#> 37.2 12.52 1 57 1 0
#> 60 13.15 1 38 1 0
#> 171.1 16.57 1 41 0 1
#> 181 16.46 1 45 0 1
#> 183.2 9.24 1 67 1 0
#> 91 5.33 1 61 0 1
#> 4 17.64 1 NA 0 1
#> 4.1 17.64 1 NA 0 1
#> 180 14.82 1 37 0 0
#> 107 11.18 1 54 1 0
#> 139 21.49 1 63 1 0
#> 171.2 16.57 1 41 0 1
#> 51.5 18.23 1 83 0 1
#> 189 10.51 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 25.1 6.32 1 34 1 0
#> 18.1 15.21 1 49 1 0
#> 189.1 10.51 1 NA 1 0
#> 117.1 17.46 1 26 0 1
#> 76.1 19.22 1 54 0 1
#> 130.1 16.47 1 53 0 1
#> 111 17.45 1 47 0 1
#> 199 19.81 1 NA 0 1
#> 192.1 16.44 1 31 1 0
#> 5 16.43 1 51 0 1
#> 89.2 11.44 1 NA 0 0
#> 100 16.07 1 60 0 0
#> 81.1 14.06 1 34 0 0
#> 97 19.14 1 65 0 1
#> 30 17.43 1 78 0 0
#> 199.1 19.81 1 NA 0 1
#> 25.2 6.32 1 34 1 0
#> 130.2 16.47 1 53 0 1
#> 50.1 10.02 1 NA 1 0
#> 192.2 16.44 1 31 1 0
#> 50.2 10.02 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 32.1 20.90 1 37 1 0
#> 24 23.89 1 38 0 0
#> 194 22.40 1 38 0 1
#> 77 7.27 1 67 0 1
#> 183.3 9.24 1 67 1 0
#> 81.2 14.06 1 34 0 0
#> 106 16.67 1 49 1 0
#> 45.1 17.42 1 54 0 1
#> 101.2 9.97 1 10 0 1
#> 79.2 16.23 1 54 1 0
#> 149 8.37 1 33 1 0
#> 106.1 16.67 1 49 1 0
#> 124 9.73 1 NA 1 0
#> 183.4 9.24 1 67 1 0
#> 130.3 16.47 1 53 0 1
#> 170 19.54 1 43 0 1
#> 133 14.65 1 57 0 0
#> 26 15.77 1 49 0 1
#> 29 15.45 1 68 1 0
#> 43 12.10 1 61 0 1
#> 129 23.41 1 53 1 0
#> 119 24.00 0 17 0 0
#> 148 24.00 0 61 1 0
#> 163 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 122 24.00 0 66 0 0
#> 17 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 161 24.00 0 45 0 0
#> 198 24.00 0 66 0 1
#> 48 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 47 24.00 0 38 0 1
#> 151 24.00 0 42 0 0
#> 20 24.00 0 46 1 0
#> 94 24.00 0 51 0 1
#> 126 24.00 0 48 0 0
#> 64 24.00 0 43 0 0
#> 3 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 174 24.00 0 49 1 0
#> 17.1 24.00 0 38 0 1
#> 174.1 24.00 0 49 1 0
#> 17.2 24.00 0 38 0 1
#> 48.1 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 120 24.00 0 68 0 1
#> 20.1 24.00 0 46 1 0
#> 11 24.00 0 42 0 1
#> 47.1 24.00 0 38 0 1
#> 137 24.00 0 45 1 0
#> 176 24.00 0 43 0 1
#> 135 24.00 0 58 1 0
#> 38.1 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 98 24.00 0 34 1 0
#> 116 24.00 0 58 0 1
#> 1 24.00 0 23 1 0
#> 67 24.00 0 25 0 0
#> 200 24.00 0 64 0 0
#> 156 24.00 0 50 1 0
#> 87 24.00 0 27 0 0
#> 115.1 24.00 0 NA 1 0
#> 27 24.00 0 63 1 0
#> 142 24.00 0 53 0 0
#> 161.1 24.00 0 45 0 0
#> 73.1 24.00 0 NA 0 1
#> 163.1 24.00 0 66 0 0
#> 119.1 24.00 0 17 0 0
#> 53 24.00 0 32 0 1
#> 22 24.00 0 52 1 0
#> 138 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 118 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 138.1 24.00 0 44 1 0
#> 3.1 24.00 0 31 1 0
#> 38.2 24.00 0 31 1 0
#> 38.3 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 198.1 24.00 0 66 0 1
#> 156.1 24.00 0 50 1 0
#> 165.1 24.00 0 47 0 0
#> 65 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 116.1 24.00 0 58 0 1
#> 198.2 24.00 0 66 0 1
#> 31 24.00 0 36 0 1
#> 3.2 24.00 0 31 1 0
#> 148.1 24.00 0 61 1 0
#> 83 24.00 0 6 0 0
#> 20.2 24.00 0 46 1 0
#> 185 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 103 24.00 0 56 1 0
#> 119.2 24.00 0 17 0 0
#> 137.1 24.00 0 45 1 0
#> 27.1 24.00 0 63 1 0
#> 174.2 24.00 0 49 1 0
#> 141 24.00 0 44 1 0
#> 151.1 24.00 0 42 0 0
#> 35 24.00 0 51 0 0
#> 151.2 24.00 0 42 0 0
#> 73.2 24.00 0 NA 0 1
#> 144.1 24.00 0 28 0 1
#> 47.2 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.16 NA NA NA
#> 2 age, Cure model 0.0163 NA NA NA
#> 3 grade_ii, Cure model 0.532 NA NA NA
#> 4 grade_iii, Cure model 0.990 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00820 NA NA NA
#> 2 grade_ii, Survival model 0.293 NA NA NA
#> 3 grade_iii, Survival model 0.00302 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.16481 0.01635 0.53159 0.99037
#>
#> Degrees of Freedom: 179 Total (i.e. Null); 176 Residual
#> Null Deviance: 248.4
#> Residual Deviance: 239.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.16481067 0.01634918 0.53159015 0.99037400
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008195561 0.293063738 0.003025000
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.131861708 0.667889826 0.593888838 0.131861708 0.806379623 0.131861708
#> [7] 0.452125241 0.071723746 0.040865629 0.085594607 0.844587158 0.092877807
#> [13] 0.024072401 0.717899941 0.521592742 0.182185324 0.258603444 0.396682303
#> [19] 0.693050926 0.857525225 0.452125241 0.717899941 0.341937322 0.191758708
#> [25] 0.793484402 0.947687290 0.755155759 0.052844738 0.278970294 0.191758708
#> [31] 0.806379623 0.059130912 0.857525225 0.059130912 0.219421827 0.486161329
#> [37] 0.693050926 0.545592775 0.123629335 0.131861708 0.396682303 0.680450203
#> [43] 0.655366692 0.131861708 0.013353253 0.606191727 0.310332427 0.046738673
#> [49] 0.191758708 0.717899941 0.642889320 0.310332427 0.385259681 0.857525225
#> [55] 0.986738050 0.569497545 0.780661084 0.018553676 0.310332427 0.131861708
#> [61] 0.115568684 0.947687290 0.545592775 0.219421827 0.092877807 0.341937322
#> [67] 0.238587711 0.396682303 0.440606621 0.497869587 0.606191727 0.107668654
#> [73] 0.248500389 0.947687290 0.341937322 0.396682303 0.030037531 0.030037531
#> [79] 0.001189348 0.008701879 0.934479433 0.857525225 0.606191727 0.289500824
#> [85] 0.258603444 0.806379623 0.452125241 0.921349665 0.289500824 0.857525225
#> [91] 0.341937322 0.078568789 0.581645472 0.509685791 0.533561420 0.767866952
#> [97] 0.004658919 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 51 14 96 51.1 101 51.2 79 105 190 55 187 76 36
#> 18.23 12.89 14.54 18.23 9.97 18.23 16.23 19.75 20.81 19.34 9.92 19.22 21.19
#> 37 125 41 45 192 154 183 79.1 37.1 130 134 93 25
#> 12.52 15.65 18.02 17.42 16.44 12.63 9.24 16.23 12.52 16.47 17.81 10.33 6.32
#> 56 128 23 134.1 101.1 158 183.1 158.1 117 188 154.1 18 88
#> 12.21 20.35 16.92 17.81 9.97 20.14 9.24 20.14 17.46 16.16 12.63 15.21 18.37
#> 51.3 85 140 155 51.4 136 81 171 68 134.2 37.2 60 171.1
#> 18.23 16.44 12.68 13.08 18.23 21.83 14.06 16.57 20.62 17.81 12.52 13.15 16.57
#> 181 183.2 91 180 107 139 171.2 51.5 179 25.1 18.1 117.1 76.1
#> 16.46 9.24 5.33 14.82 11.18 21.49 16.57 18.23 18.63 6.32 15.21 17.46 19.22
#> 130.1 111 192.1 5 100 81.1 97 30 25.2 130.2 192.2 32 32.1
#> 16.47 17.45 16.44 16.43 16.07 14.06 19.14 17.43 6.32 16.47 16.44 20.90 20.90
#> 24 194 77 183.3 81.2 106 45.1 101.2 79.2 149 106.1 183.4 130.3
#> 23.89 22.40 7.27 9.24 14.06 16.67 17.42 9.97 16.23 8.37 16.67 9.24 16.47
#> 170 133 26 29 43 129 119 148 163 122 17 12 161
#> 19.54 14.65 15.77 15.45 12.10 23.41 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 48 152 47 151 20 94 126 64 3 7 174 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.1 17.2 48.1 38 95 132 120 20.1 11 47.1 137 176 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38.1 46 98 116 1 67 200 156 87 27 142 161.1 163.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 53 22 138 144 118 165 138.1 3.1 38.2 38.3 62 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.1 165.1 65 186 116.1 198.2 31 3.2 148.1 83 20.2 185 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 119.2 137.1 27.1 174.2 141 151.1 35 151.2 144.1 47.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[95]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00998974 1.27900408 0.58667662
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.43967435 0.02498677 0.44624207
#> grade_iii, Cure model
#> 0.90902856
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 105 19.75 1 60 0 0
#> 100 16.07 1 60 0 0
#> 179 18.63 1 42 0 0
#> 32 20.90 1 37 1 0
#> 187 9.92 1 39 1 0
#> 183 9.24 1 67 1 0
#> 60 13.15 1 38 1 0
#> 153 21.33 1 55 1 0
#> 68 20.62 1 44 0 0
#> 45 17.42 1 54 0 1
#> 139 21.49 1 63 1 0
#> 15 22.68 1 48 0 0
#> 6 15.64 1 39 0 0
#> 96 14.54 1 33 0 1
#> 14 12.89 1 21 0 0
#> 183.1 9.24 1 67 1 0
#> 76 19.22 1 54 0 1
#> 24 23.89 1 38 0 0
#> 107 11.18 1 54 1 0
#> 78 23.88 1 43 0 0
#> 170 19.54 1 43 0 1
#> 195 11.76 1 NA 1 0
#> 105.1 19.75 1 60 0 0
#> 4 17.64 1 NA 0 1
#> 134 17.81 1 47 1 0
#> 97 19.14 1 65 0 1
#> 170.1 19.54 1 43 0 1
#> 140 12.68 1 59 1 0
#> 105.2 19.75 1 60 0 0
#> 57 14.46 1 45 0 1
#> 41 18.02 1 40 1 0
#> 183.2 9.24 1 67 1 0
#> 189 10.51 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 60.1 13.15 1 38 1 0
#> 107.1 11.18 1 54 1 0
#> 106 16.67 1 49 1 0
#> 51 18.23 1 83 0 1
#> 183.3 9.24 1 67 1 0
#> 97.1 19.14 1 65 0 1
#> 150 20.33 1 48 0 0
#> 188 16.16 1 46 0 1
#> 183.4 9.24 1 67 1 0
#> 76.1 19.22 1 54 0 1
#> 51.1 18.23 1 83 0 1
#> 167 15.55 1 56 1 0
#> 36 21.19 1 48 0 1
#> 170.2 19.54 1 43 0 1
#> 15.1 22.68 1 48 0 0
#> 101 9.97 1 10 0 1
#> 52 10.42 1 52 0 1
#> 133 14.65 1 57 0 0
#> 60.2 13.15 1 38 1 0
#> 111 17.45 1 47 0 1
#> 15.2 22.68 1 48 0 0
#> 108 18.29 1 39 0 1
#> 37 12.52 1 57 1 0
#> 6.1 15.64 1 39 0 0
#> 14.1 12.89 1 21 0 0
#> 110 17.56 1 65 0 1
#> 154 12.63 1 20 1 0
#> 175 21.91 1 43 0 0
#> 125 15.65 1 67 1 0
#> 164 23.60 1 76 0 1
#> 55 19.34 1 69 0 1
#> 188.1 16.16 1 46 0 1
#> 45.1 17.42 1 54 0 1
#> 187.1 9.92 1 39 1 0
#> 23 16.92 1 61 0 0
#> 29 15.45 1 68 1 0
#> 96.1 14.54 1 33 0 1
#> 169 22.41 1 46 0 0
#> 85 16.44 1 36 0 0
#> 18 15.21 1 49 1 0
#> 168 23.72 1 70 0 0
#> 114 13.68 1 NA 0 0
#> 167.1 15.55 1 56 1 0
#> 130 16.47 1 53 0 1
#> 56 12.21 1 60 0 0
#> 32.1 20.90 1 37 1 0
#> 15.3 22.68 1 48 0 0
#> 30 17.43 1 78 0 0
#> 16 8.71 1 71 0 1
#> 158 20.14 1 74 1 0
#> 124 9.73 1 NA 1 0
#> 51.2 18.23 1 83 0 1
#> 158.1 20.14 1 74 1 0
#> 66 22.13 1 53 0 0
#> 16.1 8.71 1 71 0 1
#> 92 22.92 1 47 0 1
#> 169.1 22.41 1 46 0 0
#> 168.1 23.72 1 70 0 0
#> 39 15.59 1 37 0 1
#> 107.2 11.18 1 54 1 0
#> 76.2 19.22 1 54 0 1
#> 77 7.27 1 67 0 1
#> 15.4 22.68 1 48 0 0
#> 145 10.07 1 65 1 0
#> 6.2 15.64 1 39 0 0
#> 30.1 17.43 1 78 0 0
#> 167.2 15.55 1 56 1 0
#> 106.1 16.67 1 49 1 0
#> 93 10.33 1 52 0 1
#> 164.1 23.60 1 76 0 1
#> 117 17.46 1 26 0 1
#> 86 23.81 1 58 0 1
#> 166 19.98 1 48 0 0
#> 92.1 22.92 1 47 0 1
#> 113 22.86 1 34 0 0
#> 158.2 20.14 1 74 1 0
#> 194 22.40 1 38 0 1
#> 149 8.37 1 33 1 0
#> 137 24.00 0 45 1 0
#> 19 24.00 0 57 0 1
#> 38 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 53 24.00 0 32 0 1
#> 7 24.00 0 37 1 0
#> 109 24.00 0 48 0 0
#> 62 24.00 0 71 0 0
#> 191 24.00 0 60 0 1
#> 11 24.00 0 42 0 1
#> 34 24.00 0 36 0 0
#> 121 24.00 0 57 1 0
#> 34.1 24.00 0 36 0 0
#> 27 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 95 24.00 0 68 0 1
#> 33 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 33.1 24.00 0 53 0 0
#> 173 24.00 0 19 0 1
#> 67 24.00 0 25 0 0
#> 7.1 24.00 0 37 1 0
#> 35 24.00 0 51 0 0
#> 200.1 24.00 0 64 0 0
#> 71 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 98 24.00 0 34 1 0
#> 185 24.00 0 44 1 0
#> 95.1 24.00 0 68 0 1
#> 28 24.00 0 67 1 0
#> 2 24.00 0 9 0 0
#> 98.1 24.00 0 34 1 0
#> 20.1 24.00 0 46 1 0
#> 62.1 24.00 0 71 0 0
#> 173.1 24.00 0 19 0 1
#> 173.2 24.00 0 19 0 1
#> 74 24.00 0 43 0 1
#> 152 24.00 0 36 0 1
#> 98.2 24.00 0 34 1 0
#> 147 24.00 0 76 1 0
#> 131 24.00 0 66 0 0
#> 31 24.00 0 36 0 1
#> 84 24.00 0 39 0 1
#> 172 24.00 0 41 0 0
#> 163 24.00 0 66 0 0
#> 200.2 24.00 0 64 0 0
#> 152.1 24.00 0 36 0 1
#> 185.1 24.00 0 44 1 0
#> 172.1 24.00 0 41 0 0
#> 62.2 24.00 0 71 0 0
#> 64 24.00 0 43 0 0
#> 196 24.00 0 19 0 0
#> 74.1 24.00 0 43 0 1
#> 64.1 24.00 0 43 0 0
#> 200.3 24.00 0 64 0 0
#> 104 24.00 0 50 1 0
#> 147.1 24.00 0 76 1 0
#> 75 24.00 0 21 1 0
#> 46 24.00 0 71 0 0
#> 200.4 24.00 0 64 0 0
#> 34.2 24.00 0 36 0 0
#> 115 24.00 0 NA 1 0
#> 31.1 24.00 0 36 0 1
#> 174 24.00 0 49 1 0
#> 142 24.00 0 53 0 0
#> 83 24.00 0 6 0 0
#> 98.3 24.00 0 34 1 0
#> 122 24.00 0 66 0 0
#> 135 24.00 0 58 1 0
#> 71.1 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 11.1 24.00 0 42 0 1
#> 141.1 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 142.1 24.00 0 53 0 0
#> 35.1 24.00 0 51 0 0
#> 142.2 24.00 0 53 0 0
#> 141.2 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 53.1 24.00 0 32 0 1
#> 174.1 24.00 0 49 1 0
#> 119 24.00 0 17 0 0
#> 20.2 24.00 0 46 1 0
#> 122.1 24.00 0 66 0 0
#> 62.3 24.00 0 71 0 0
#> 151 24.00 0 42 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.44 NA NA NA
#> 2 age, Cure model 0.0250 NA NA NA
#> 3 grade_ii, Cure model 0.446 NA NA NA
#> 4 grade_iii, Cure model 0.909 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00999 NA NA NA
#> 2 grade_ii, Survival model 1.28 NA NA NA
#> 3 grade_iii, Survival model 0.587 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.43967 0.02499 0.44624 0.90903
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 254.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.43967435 0.02498677 0.44624207 0.90902856
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00998974 1.27900408 0.58667662
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.320047912 0.643767313 0.439071510 0.240663240 0.919217780 0.934407817
#> [7] 0.781154107 0.217016645 0.260811430 0.557713032 0.204419911 0.089546310
#> [13] 0.662763907 0.754585177 0.806259568 0.934407817 0.389617362 0.001581715
#> [19] 0.856150540 0.006822488 0.349982224 0.320047912 0.499470021 0.419112318
#> [25] 0.349982224 0.823151344 0.320047912 0.772273665 0.489506439 0.934407817
#> [31] 0.895635453 0.781154107 0.856150540 0.587049816 0.459373247 0.934407817
#> [37] 0.419112318 0.271234086 0.624921791 0.934407817 0.389617362 0.459373247
#> [43] 0.700602817 0.228874413 0.349982224 0.089546310 0.911405265 0.879764630
#> [49] 0.745626587 0.781154107 0.528587947 0.089546310 0.449247354 0.839796784
#> [55] 0.662763907 0.806259568 0.509191829 0.831554953 0.191071157 0.653323594
#> [61] 0.040276839 0.379488944 0.624921791 0.557713032 0.919217780 0.577164210
#> [67] 0.727670852 0.754585177 0.140641599 0.615387640 0.736714486 0.022115426
#> [73] 0.700602817 0.605897902 0.847955887 0.240663240 0.089546310 0.538229062
#> [79] 0.970697896 0.281811599 0.459373247 0.281811599 0.178040537 0.970697896
#> [85] 0.059994353 0.140641599 0.022115426 0.691068219 0.856150540 0.389617362
#> [91] 0.992700739 0.089546310 0.903550531 0.662763907 0.538229062 0.700602817
#> [97] 0.587049816 0.887702507 0.040276839 0.518924930 0.014430304 0.310172278
#> [103] 0.059994353 0.078999296 0.281811599 0.165390738 0.985405733 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000
#>
#> $Time
#> 105 100 179 32 187 183 60 153 68 45 139 15 6
#> 19.75 16.07 18.63 20.90 9.92 9.24 13.15 21.33 20.62 17.42 21.49 22.68 15.64
#> 96 14 183.1 76 24 107 78 170 105.1 134 97 170.1 140
#> 14.54 12.89 9.24 19.22 23.89 11.18 23.88 19.54 19.75 17.81 19.14 19.54 12.68
#> 105.2 57 41 183.2 61 60.1 107.1 106 51 183.3 97.1 150 188
#> 19.75 14.46 18.02 9.24 10.12 13.15 11.18 16.67 18.23 9.24 19.14 20.33 16.16
#> 183.4 76.1 51.1 167 36 170.2 15.1 101 52 133 60.2 111 15.2
#> 9.24 19.22 18.23 15.55 21.19 19.54 22.68 9.97 10.42 14.65 13.15 17.45 22.68
#> 108 37 6.1 14.1 110 154 175 125 164 55 188.1 45.1 187.1
#> 18.29 12.52 15.64 12.89 17.56 12.63 21.91 15.65 23.60 19.34 16.16 17.42 9.92
#> 23 29 96.1 169 85 18 168 167.1 130 56 32.1 15.3 30
#> 16.92 15.45 14.54 22.41 16.44 15.21 23.72 15.55 16.47 12.21 20.90 22.68 17.43
#> 16 158 51.2 158.1 66 16.1 92 169.1 168.1 39 107.2 76.2 77
#> 8.71 20.14 18.23 20.14 22.13 8.71 22.92 22.41 23.72 15.59 11.18 19.22 7.27
#> 15.4 145 6.2 30.1 167.2 106.1 93 164.1 117 86 166 92.1 113
#> 22.68 10.07 15.64 17.43 15.55 16.67 10.33 23.60 17.46 23.81 19.98 22.92 22.86
#> 158.2 194 149 137 19 38 176 53 7 109 62 191 11
#> 20.14 22.40 8.37 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 121 34.1 27 116 95 33 200 33.1 173 67 7.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.1 71 20 98 185 95.1 28 2 98.1 20.1 62.1 173.1 173.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 152 98.2 147 131 31 84 172 163 200.2 152.1 185.1 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.2 64 196 74.1 64.1 200.3 104 147.1 75 46 200.4 34.2 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 142 83 98.3 122 135 71.1 118 141 11.1 141.1 162 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 35.1 142.2 141.2 21 53.1 174.1 119 20.2 122.1 62.3 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[96]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006794256 0.616127743 0.357662934
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.64204640 0.01343692 -0.01875302
#> grade_iii, Cure model
#> 0.55115038
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 86 23.81 1 58 0 1
#> 86.1 23.81 1 58 0 1
#> 168 23.72 1 70 0 0
#> 181 16.46 1 45 0 1
#> 111 17.45 1 47 0 1
#> 49 12.19 1 48 1 0
#> 166 19.98 1 48 0 0
#> 123 13.00 1 44 1 0
#> 85 16.44 1 36 0 0
#> 194 22.40 1 38 0 1
#> 8 18.43 1 32 0 0
#> 175 21.91 1 43 0 0
#> 76 19.22 1 54 0 1
#> 167 15.55 1 56 1 0
#> 96 14.54 1 33 0 1
#> 45 17.42 1 54 0 1
#> 166.1 19.98 1 48 0 0
#> 134 17.81 1 47 1 0
#> 195 11.76 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 194.1 22.40 1 38 0 1
#> 114 13.68 1 NA 0 0
#> 197 21.60 1 69 1 0
#> 18 15.21 1 49 1 0
#> 167.1 15.55 1 56 1 0
#> 86.2 23.81 1 58 0 1
#> 58 19.34 1 39 0 0
#> 36 21.19 1 48 0 1
#> 58.1 19.34 1 39 0 0
#> 77 7.27 1 67 0 1
#> 61 10.12 1 36 0 1
#> 91.1 5.33 1 61 0 1
#> 63 22.77 1 31 1 0
#> 52 10.42 1 52 0 1
#> 159 10.55 1 50 0 1
#> 180 14.82 1 37 0 0
#> 49.1 12.19 1 48 1 0
#> 66 22.13 1 53 0 0
#> 150 20.33 1 48 0 0
#> 57 14.46 1 45 0 1
#> 5 16.43 1 51 0 1
#> 113 22.86 1 34 0 0
#> 197.1 21.60 1 69 1 0
#> 187 9.92 1 39 1 0
#> 145 10.07 1 65 1 0
#> 89 11.44 1 NA 0 0
#> 88 18.37 1 47 0 0
#> 49.2 12.19 1 48 1 0
#> 100 16.07 1 60 0 0
#> 177 12.53 1 75 0 0
#> 136 21.83 1 43 0 1
#> 15 22.68 1 48 0 0
#> 190 20.81 1 42 1 0
#> 199 19.81 1 NA 0 1
#> 40 18.00 1 28 1 0
#> 5.1 16.43 1 51 0 1
#> 8.1 18.43 1 32 0 0
#> 130 16.47 1 53 0 1
#> 181.1 16.46 1 45 0 1
#> 167.2 15.55 1 56 1 0
#> 57.1 14.46 1 45 0 1
#> 97 19.14 1 65 0 1
#> 169 22.41 1 46 0 0
#> 100.1 16.07 1 60 0 0
#> 18.1 15.21 1 49 1 0
#> 197.2 21.60 1 69 1 0
#> 100.2 16.07 1 60 0 0
#> 89.1 11.44 1 NA 0 0
#> 145.1 10.07 1 65 1 0
#> 57.2 14.46 1 45 0 1
#> 37 12.52 1 57 1 0
#> 139 21.49 1 63 1 0
#> 155 13.08 1 26 0 0
#> 177.1 12.53 1 75 0 0
#> 197.3 21.60 1 69 1 0
#> 13 14.34 1 54 0 1
#> 77.1 7.27 1 67 0 1
#> 134.1 17.81 1 47 1 0
#> 134.2 17.81 1 47 1 0
#> 175.1 21.91 1 43 0 0
#> 78 23.88 1 43 0 0
#> 49.3 12.19 1 48 1 0
#> 41 18.02 1 40 1 0
#> 68 20.62 1 44 0 0
#> 59 10.16 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 66.1 22.13 1 53 0 0
#> 61.1 10.12 1 36 0 1
#> 101 9.97 1 10 0 1
#> 179 18.63 1 42 0 0
#> 195.1 11.76 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 180.1 14.82 1 37 0 0
#> 76.1 19.22 1 54 0 1
#> 77.2 7.27 1 67 0 1
#> 96.1 14.54 1 33 0 1
#> 194.2 22.40 1 38 0 1
#> 29 15.45 1 68 1 0
#> 101.1 9.97 1 10 0 1
#> 106 16.67 1 49 1 0
#> 91.2 5.33 1 61 0 1
#> 29.1 15.45 1 68 1 0
#> 15.1 22.68 1 48 0 0
#> 69.1 23.23 1 25 0 1
#> 49.4 12.19 1 48 1 0
#> 195.2 11.76 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 91.3 5.33 1 61 0 1
#> 124 9.73 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 37.1 12.52 1 57 1 0
#> 69.2 23.23 1 25 0 1
#> 148 24.00 0 61 1 0
#> 196 24.00 0 19 0 0
#> 146 24.00 0 63 1 0
#> 165 24.00 0 47 0 0
#> 1 24.00 0 23 1 0
#> 95 24.00 0 68 0 1
#> 191 24.00 0 60 0 1
#> 118 24.00 0 44 1 0
#> 146.1 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 20 24.00 0 46 1 0
#> 174 24.00 0 49 1 0
#> 98 24.00 0 34 1 0
#> 196.1 24.00 0 19 0 0
#> 165.1 24.00 0 47 0 0
#> 22 24.00 0 52 1 0
#> 200 24.00 0 64 0 0
#> 84 24.00 0 39 0 1
#> 174.1 24.00 0 49 1 0
#> 173 24.00 0 19 0 1
#> 22.1 24.00 0 52 1 0
#> 27 24.00 0 63 1 0
#> 11 24.00 0 42 0 1
#> 160 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 160.1 24.00 0 31 1 0
#> 191.1 24.00 0 60 0 1
#> 152 24.00 0 36 0 1
#> 135.1 24.00 0 58 1 0
#> 103 24.00 0 56 1 0
#> 182 24.00 0 35 0 0
#> 20.1 24.00 0 46 1 0
#> 151 24.00 0 42 0 0
#> 200.1 24.00 0 64 0 0
#> 28 24.00 0 67 1 0
#> 47 24.00 0 38 0 1
#> 11.1 24.00 0 42 0 1
#> 71 24.00 0 51 0 0
#> 165.2 24.00 0 47 0 0
#> 31 24.00 0 36 0 1
#> 31.1 24.00 0 36 0 1
#> 191.2 24.00 0 60 0 1
#> 116 24.00 0 58 0 1
#> 47.1 24.00 0 38 0 1
#> 54 24.00 0 53 1 0
#> 200.2 24.00 0 64 0 0
#> 109 24.00 0 48 0 0
#> 121 24.00 0 57 1 0
#> 182.1 24.00 0 35 0 0
#> 95.1 24.00 0 68 0 1
#> 121.1 24.00 0 57 1 0
#> 74 24.00 0 43 0 1
#> 193 24.00 0 45 0 1
#> 142 24.00 0 53 0 0
#> 115 24.00 0 NA 1 0
#> 38 24.00 0 31 1 0
#> 191.3 24.00 0 60 0 1
#> 83 24.00 0 6 0 0
#> 83.1 24.00 0 6 0 0
#> 84.1 24.00 0 39 0 1
#> 84.2 24.00 0 39 0 1
#> 80 24.00 0 41 0 0
#> 31.2 24.00 0 36 0 1
#> 186 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 121.2 24.00 0 57 1 0
#> 137 24.00 0 45 1 0
#> 34 24.00 0 36 0 0
#> 53 24.00 0 32 0 1
#> 34.1 24.00 0 36 0 0
#> 71.1 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 64.1 24.00 0 43 0 0
#> 191.4 24.00 0 60 0 1
#> 80.1 24.00 0 41 0 0
#> 172 24.00 0 41 0 0
#> 115.1 24.00 0 NA 1 0
#> 33 24.00 0 53 0 0
#> 121.3 24.00 0 57 1 0
#> 191.5 24.00 0 60 0 1
#> 126 24.00 0 48 0 0
#> 148.1 24.00 0 61 1 0
#> 19 24.00 0 57 0 1
#> 62 24.00 0 71 0 0
#> 196.2 24.00 0 19 0 0
#> 131.1 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.642 NA NA NA
#> 2 age, Cure model 0.0134 NA NA NA
#> 3 grade_ii, Cure model -0.0188 NA NA NA
#> 4 grade_iii, Cure model 0.551 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00679 NA NA NA
#> 2 grade_ii, Survival model 0.616 NA NA NA
#> 3 grade_iii, Survival model 0.358 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.64205 0.01344 -0.01875 0.55115
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.9
#> Residual Deviance: 254.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.64204640 0.01343692 -0.01875302 0.55115038
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006794256 0.616127743 0.357662934
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.12969554 0.12969554 0.19147058 0.70199004 0.67264117 0.88324289
#> [7] 0.53038916 0.85474584 0.71603535 0.34105226 0.60072007 0.40593056
#> [13] 0.56633686 0.75703381 0.81333416 0.68012505 0.53038916 0.64232383
#> [19] 0.97604914 0.34105226 0.44361630 0.78891783 0.75703381 0.12969554
#> [25] 0.54845233 0.49289010 0.54845233 0.96131003 0.92558630 0.97604914
#> [31] 0.27990106 0.92032763 0.91503766 0.80115258 0.88324289 0.38016518
#> [37] 0.52115709 0.82537342 0.72307356 0.26258006 0.44361630 0.95627431
#> [43] 0.93597648 0.61752357 0.88324289 0.73680949 0.86055294 0.43115342
#> [49] 0.29594598 0.50250679 0.63419745 0.72307356 0.60072007 0.69479572
#> [55] 0.70199004 0.75703381 0.82537342 0.58364018 0.32594944 0.73680949
#> [61] 0.78891783 0.44361630 0.73680949 0.93597648 0.82537342 0.87202538
#> [67] 0.48308569 0.84887909 0.86055294 0.44361630 0.84300448 0.96131003
#> [73] 0.64232383 0.64232383 0.40593056 0.06146915 0.88324289 0.62593990
#> [79] 0.51186153 0.99520379 0.38016518 0.92558630 0.94615427 0.59220046
#> [85] 0.21318117 0.80115258 0.56633686 0.96131003 0.81333416 0.34105226
#> [91] 0.77637512 0.94615427 0.68752233 0.97604914 0.77637512 0.29594598
#> [97] 0.21318117 0.88324289 0.90971666 0.97604914 0.66507583 0.87202538
#> [103] 0.21318117 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 86 86.1 168 181 111 49 166 123 85 194 8 175 76
#> 23.81 23.81 23.72 16.46 17.45 12.19 19.98 13.00 16.44 22.40 18.43 21.91 19.22
#> 167 96 45 166.1 134 91 194.1 197 18 167.1 86.2 58 36
#> 15.55 14.54 17.42 19.98 17.81 5.33 22.40 21.60 15.21 15.55 23.81 19.34 21.19
#> 58.1 77 61 91.1 63 52 159 180 49.1 66 150 57 5
#> 19.34 7.27 10.12 5.33 22.77 10.42 10.55 14.82 12.19 22.13 20.33 14.46 16.43
#> 113 197.1 187 145 88 49.2 100 177 136 15 190 40 5.1
#> 22.86 21.60 9.92 10.07 18.37 12.19 16.07 12.53 21.83 22.68 20.81 18.00 16.43
#> 8.1 130 181.1 167.2 57.1 97 169 100.1 18.1 197.2 100.2 145.1 57.2
#> 18.43 16.47 16.46 15.55 14.46 19.14 22.41 16.07 15.21 21.60 16.07 10.07 14.46
#> 37 139 155 177.1 197.3 13 77.1 134.1 134.2 175.1 78 49.3 41
#> 12.52 21.49 13.08 12.53 21.60 14.34 7.27 17.81 17.81 21.91 23.88 12.19 18.02
#> 68 127 66.1 61.1 101 179 69 180.1 76.1 77.2 96.1 194.2 29
#> 20.62 3.53 22.13 10.12 9.97 18.63 23.23 14.82 19.22 7.27 14.54 22.40 15.45
#> 101.1 106 91.2 29.1 15.1 69.1 49.4 43 91.3 110 37.1 69.2 148
#> 9.97 16.67 5.33 15.45 22.68 23.23 12.19 12.10 5.33 17.56 12.52 23.23 24.00
#> 196 146 165 1 95 191 118 146.1 64 20 174 98 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 22 200 84 174.1 173 22.1 27 11 160 135 160.1 191.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 135.1 103 182 20.1 151 200.1 28 47 11.1 71 165.2 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 191.2 116 47.1 54 200.2 109 121 182.1 95.1 121.1 74 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 38 191.3 83 83.1 84.1 84.2 80 31.2 186 65 121.2 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 53 34.1 71.1 131 64.1 191.4 80.1 172 33 121.3 191.5 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 19 62 196.2 131.1 185
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[97]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01235343 0.40661918 0.02593833
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.099778529 0.008373563 -0.360317461
#> grade_iii, Cure model
#> 0.056320206
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 110 17.56 1 65 0 1
#> 164 23.60 1 76 0 1
#> 108 18.29 1 39 0 1
#> 36 21.19 1 48 0 1
#> 30 17.43 1 78 0 0
#> 68 20.62 1 44 0 0
#> 76 19.22 1 54 0 1
#> 105 19.75 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 63 22.77 1 31 1 0
#> 150 20.33 1 48 0 0
#> 43 12.10 1 61 0 1
#> 85 16.44 1 36 0 0
#> 123 13.00 1 44 1 0
#> 86 23.81 1 58 0 1
#> 36.1 21.19 1 48 0 1
#> 140 12.68 1 59 1 0
#> 59 10.16 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 189 10.51 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 108.1 18.29 1 39 0 1
#> 92 22.92 1 47 0 1
#> 42 12.43 1 49 0 1
#> 170 19.54 1 43 0 1
#> 6 15.64 1 39 0 0
#> 179 18.63 1 42 0 0
#> 101 9.97 1 10 0 1
#> 86.1 23.81 1 58 0 1
#> 51 18.23 1 83 0 1
#> 40 18.00 1 28 1 0
#> 78 23.88 1 43 0 0
#> 134 17.81 1 47 1 0
#> 77 7.27 1 67 0 1
#> 155 13.08 1 26 0 0
#> 23 16.92 1 61 0 0
#> 76.1 19.22 1 54 0 1
#> 134.1 17.81 1 47 1 0
#> 30.1 17.43 1 78 0 0
#> 169 22.41 1 46 0 0
#> 70 7.38 1 30 1 0
#> 124 9.73 1 NA 1 0
#> 76.2 19.22 1 54 0 1
#> 190 20.81 1 42 1 0
#> 41 18.02 1 40 1 0
#> 4 17.64 1 NA 0 1
#> 26 15.77 1 49 0 1
#> 26.1 15.77 1 49 0 1
#> 16 8.71 1 71 0 1
#> 145 10.07 1 65 1 0
#> 190.1 20.81 1 42 1 0
#> 99 21.19 1 38 0 1
#> 4.1 17.64 1 NA 0 1
#> 149 8.37 1 33 1 0
#> 190.2 20.81 1 42 1 0
#> 32 20.90 1 37 1 0
#> 70.1 7.38 1 30 1 0
#> 199 19.81 1 NA 0 1
#> 90 20.94 1 50 0 1
#> 30.2 17.43 1 78 0 0
#> 157 15.10 1 47 0 0
#> 25 6.32 1 34 1 0
#> 192 16.44 1 31 1 0
#> 197 21.60 1 69 1 0
#> 23.1 16.92 1 61 0 0
#> 32.1 20.90 1 37 1 0
#> 66 22.13 1 53 0 0
#> 15 22.68 1 48 0 0
#> 187 9.92 1 39 1 0
#> 184 17.77 1 38 0 0
#> 101.1 9.97 1 10 0 1
#> 81 14.06 1 34 0 0
#> 92.1 22.92 1 47 0 1
#> 56 12.21 1 60 0 0
#> 90.1 20.94 1 50 0 1
#> 78.1 23.88 1 43 0 0
#> 56.1 12.21 1 60 0 0
#> 114.1 13.68 1 NA 0 0
#> 52 10.42 1 52 0 1
#> 114.2 13.68 1 NA 0 0
#> 37 12.52 1 57 1 0
#> 189.1 10.51 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 40.1 18.00 1 28 1 0
#> 105.1 19.75 1 60 0 0
#> 66.1 22.13 1 53 0 0
#> 58 19.34 1 39 0 0
#> 13 14.34 1 54 0 1
#> 55 19.34 1 69 0 1
#> 194 22.40 1 38 0 1
#> 192.1 16.44 1 31 1 0
#> 10 10.53 1 34 0 0
#> 111 17.45 1 47 0 1
#> 40.2 18.00 1 28 1 0
#> 96 14.54 1 33 0 1
#> 170.1 19.54 1 43 0 1
#> 8 18.43 1 32 0 0
#> 60 13.15 1 38 1 0
#> 39 15.59 1 37 0 1
#> 195 11.76 1 NA 1 0
#> 195.1 11.76 1 NA 1 0
#> 197.1 21.60 1 69 1 0
#> 101.2 9.97 1 10 0 1
#> 179.1 18.63 1 42 0 0
#> 167 15.55 1 56 1 0
#> 93 10.33 1 52 0 1
#> 149.1 8.37 1 33 1 0
#> 18 15.21 1 49 1 0
#> 154 12.63 1 20 1 0
#> 199.1 19.81 1 NA 0 1
#> 56.2 12.21 1 60 0 0
#> 164.1 23.60 1 76 0 1
#> 118 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 144 24.00 0 28 0 1
#> 191 24.00 0 60 0 1
#> 148 24.00 0 61 1 0
#> 186 24.00 0 45 1 0
#> 174 24.00 0 49 1 0
#> 120 24.00 0 68 0 1
#> 148.1 24.00 0 61 1 0
#> 64 24.00 0 43 0 0
#> 193 24.00 0 45 0 1
#> 141 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 112 24.00 0 61 0 0
#> 115 24.00 0 NA 1 0
#> 176 24.00 0 43 0 1
#> 3 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 74 24.00 0 43 0 1
#> 156 24.00 0 50 1 0
#> 135 24.00 0 58 1 0
#> 2.1 24.00 0 9 0 0
#> 54 24.00 0 53 1 0
#> 112.1 24.00 0 61 0 0
#> 72 24.00 0 40 0 1
#> 118.1 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 141.1 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 9 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 118.2 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 165 24.00 0 47 0 0
#> 95 24.00 0 68 0 1
#> 131 24.00 0 66 0 0
#> 9.1 24.00 0 31 1 0
#> 115.1 24.00 0 NA 1 0
#> 98 24.00 0 34 1 0
#> 138.1 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 22 24.00 0 52 1 0
#> 193.1 24.00 0 45 0 1
#> 104 24.00 0 50 1 0
#> 116 24.00 0 58 0 1
#> 115.2 24.00 0 NA 1 0
#> 152 24.00 0 36 0 1
#> 12.1 24.00 0 63 0 0
#> 75 24.00 0 21 1 0
#> 103 24.00 0 56 1 0
#> 73.1 24.00 0 NA 0 1
#> 186.1 24.00 0 45 1 0
#> 118.3 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 118.4 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 19.1 24.00 0 57 0 1
#> 17 24.00 0 38 0 1
#> 186.2 24.00 0 45 1 0
#> 109.1 24.00 0 48 0 0
#> 34 24.00 0 36 0 0
#> 152.1 24.00 0 36 0 1
#> 17.1 24.00 0 38 0 1
#> 74.1 24.00 0 43 0 1
#> 109.2 24.00 0 48 0 0
#> 144.1 24.00 0 28 0 1
#> 84 24.00 0 39 0 1
#> 22.1 24.00 0 52 1 0
#> 174.1 24.00 0 49 1 0
#> 178 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 118.5 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 138.2 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 162 24.00 0 51 0 0
#> 94.1 24.00 0 51 0 1
#> 71.1 24.00 0 51 0 0
#> 74.2 24.00 0 43 0 1
#> 104.1 24.00 0 50 1 0
#> 31 24.00 0 36 0 1
#> 33 24.00 0 53 0 0
#> 65 24.00 0 57 1 0
#> 33.1 24.00 0 53 0 0
#> 67 24.00 0 25 0 0
#> 196 24.00 0 19 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0998 NA NA NA
#> 2 age, Cure model 0.00837 NA NA NA
#> 3 grade_ii, Cure model -0.360 NA NA NA
#> 4 grade_iii, Cure model 0.0563 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0124 NA NA NA
#> 2 grade_ii, Survival model 0.407 NA NA NA
#> 3 grade_iii, Survival model 0.0259 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.099779 0.008374 -0.360317 0.056320
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 250.9
#> Residual Deviance: 248.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.099778529 0.008373563 -0.360317461 0.056320206
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01235343 0.40661918 0.02593833
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3611046183 0.0059341004 0.2572827087 0.0589851286 0.3830925459
#> [6] 0.1261036386 0.2000913402 0.1492214999 0.0188387940 0.1336160954
#> [11] 0.7655629635 0.4407888229 0.6560559699 0.0023693283 0.0589851286
#> [16] 0.6695580563 0.5763738701 0.1413224300 0.2572827087 0.0116070307
#> [21] 0.7102655647 0.1654793990 0.5128192039 0.2277359599 0.8378872951
#> [26] 0.0023693283 0.2776003923 0.2988365904 0.0004324184 0.3294239655
#> [31] 0.9700150934 0.6425893592 0.4171036157 0.2000913402 0.3294239655
#> [36] 0.3830925459 0.0272541495 0.9405143643 0.2000913402 0.1053689552
#> [41] 0.2882020804 0.4882821900 0.4882821900 0.8960913068 0.8232162471
#> [46] 0.1053689552 0.0589851286 0.9109797404 0.1053689552 0.0913596170
#> [51] 0.9405143643 0.0774591354 0.3830925459 0.5634773045 0.9850060261
#> [56] 0.4407888229 0.0474987414 0.4171036157 0.0913596170 0.0369382694
#> [61] 0.0228730434 0.8813433004 0.3503555129 0.8378872951 0.6158276569
#> [66] 0.0116070307 0.7239800255 0.0774591354 0.0004324184 0.7239800255
#> [71] 0.7941643545 0.6966665799 0.4761277277 0.2988365904 0.1492214999
#> [76] 0.0369382694 0.1823974323 0.6025543291 0.1823974323 0.0319644845
#> [81] 0.4407888229 0.7798186853 0.3720294195 0.2988365904 0.5894179713
#> [86] 0.1654793990 0.2472124723 0.6291998410 0.5253541492 0.0474987414
#> [91] 0.8378872951 0.2277359599 0.5379947351 0.8086302661 0.9109797404
#> [96] 0.5507094540 0.6831355734 0.7239800255 0.0059341004 0.0000000000
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000
#>
#> $Time
#> 110 164 108 36 30 68 76 105 63 150 43 85 123
#> 17.56 23.60 18.29 21.19 17.43 20.62 19.22 19.75 22.77 20.33 12.10 16.44 13.00
#> 86 36.1 140 133 166 108.1 92 42 170 6 179 101 86.1
#> 23.81 21.19 12.68 14.65 19.98 18.29 22.92 12.43 19.54 15.64 18.63 9.97 23.81
#> 51 40 78 134 77 155 23 76.1 134.1 30.1 169 70 76.2
#> 18.23 18.00 23.88 17.81 7.27 13.08 16.92 19.22 17.81 17.43 22.41 7.38 19.22
#> 190 41 26 26.1 16 145 190.1 99 149 190.2 32 70.1 90
#> 20.81 18.02 15.77 15.77 8.71 10.07 20.81 21.19 8.37 20.81 20.90 7.38 20.94
#> 30.2 157 25 192 197 23.1 32.1 66 15 187 184 101.1 81
#> 17.43 15.10 6.32 16.44 21.60 16.92 20.90 22.13 22.68 9.92 17.77 9.97 14.06
#> 92.1 56 90.1 78.1 56.1 52 37 79 40.1 105.1 66.1 58 13
#> 22.92 12.21 20.94 23.88 12.21 10.42 12.52 16.23 18.00 19.75 22.13 19.34 14.34
#> 55 194 192.1 10 111 40.2 96 170.1 8 60 39 197.1 101.2
#> 19.34 22.40 16.44 10.53 17.45 18.00 14.54 19.54 18.43 13.15 15.59 21.60 9.97
#> 179.1 167 93 149.1 18 154 56.2 164.1 118 144 191 148 186
#> 18.63 15.55 10.33 8.37 15.21 12.63 12.21 23.60 24.00 24.00 24.00 24.00 24.00
#> 174 120 148.1 64 193 141 2 112 176 3 62 74 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 2.1 54 112.1 72 118.1 71 138 53 141.1 47 9 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118.2 119 165 95 131 9.1 98 138.1 12 22 193.1 104 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 12.1 75 103 186.1 118.3 182 118.4 109 19.1 17 186.2 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 152.1 17.1 74.1 109.2 144.1 84 22.1 174.1 178 94 118.5 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.2 11 162 94.1 71.1 74.2 104.1 31 33 65 33.1 67 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[98]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001772883 0.796146239 0.717790374
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.82049124 0.02007463 -0.26720408
#> grade_iii, Cure model
#> 0.32276606
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 128 20.35 1 35 0 1
#> 195 11.76 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 169 22.41 1 46 0 0
#> 66 22.13 1 53 0 0
#> 180 14.82 1 37 0 0
#> 39 15.59 1 37 0 1
#> 59 10.16 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 43 12.10 1 61 0 1
#> 66.1 22.13 1 53 0 0
#> 194 22.40 1 38 0 1
#> 149 8.37 1 33 1 0
#> 153 21.33 1 55 1 0
#> 59.1 10.16 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 139 21.49 1 63 1 0
#> 129 23.41 1 53 1 0
#> 61 10.12 1 36 0 1
#> 125 15.65 1 67 1 0
#> 8 18.43 1 32 0 0
#> 89 11.44 1 NA 0 0
#> 89.1 11.44 1 NA 0 0
#> 29 15.45 1 68 1 0
#> 55 19.34 1 69 0 1
#> 56 12.21 1 60 0 0
#> 149.1 8.37 1 33 1 0
#> 169.1 22.41 1 46 0 0
#> 183 9.24 1 67 1 0
#> 133 14.65 1 57 0 0
#> 114 13.68 1 NA 0 0
#> 68 20.62 1 44 0 0
#> 78 23.88 1 43 0 0
#> 56.1 12.21 1 60 0 0
#> 123 13.00 1 44 1 0
#> 136 21.83 1 43 0 1
#> 43.1 12.10 1 61 0 1
#> 59.2 10.16 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 30 17.43 1 78 0 0
#> 168 23.72 1 70 0 0
#> 8.1 18.43 1 32 0 0
#> 101 9.97 1 10 0 1
#> 111 17.45 1 47 0 1
#> 194.1 22.40 1 38 0 1
#> 63 22.77 1 31 1 0
#> 130 16.47 1 53 0 1
#> 68.1 20.62 1 44 0 0
#> 150 20.33 1 48 0 0
#> 106 16.67 1 49 1 0
#> 175.1 21.91 1 43 0 0
#> 45 17.42 1 54 0 1
#> 13 14.34 1 54 0 1
#> 24 23.89 1 38 0 0
#> 23 16.92 1 61 0 0
#> 157 15.10 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 10 10.53 1 34 0 0
#> 90 20.94 1 50 0 1
#> 153.1 21.33 1 55 1 0
#> 32 20.90 1 37 1 0
#> 24.1 23.89 1 38 0 0
#> 92 22.92 1 47 0 1
#> 194.2 22.40 1 38 0 1
#> 127 3.53 1 62 0 1
#> 16 8.71 1 71 0 1
#> 5 16.43 1 51 0 1
#> 89.2 11.44 1 NA 0 0
#> 155 13.08 1 26 0 0
#> 55.1 19.34 1 69 0 1
#> 16.1 8.71 1 71 0 1
#> 108 18.29 1 39 0 1
#> 158 20.14 1 74 1 0
#> 114.1 13.68 1 NA 0 0
#> 43.2 12.10 1 61 0 1
#> 187 9.92 1 39 1 0
#> 101.1 9.97 1 10 0 1
#> 123.1 13.00 1 44 1 0
#> 51 18.23 1 83 0 1
#> 177 12.53 1 75 0 0
#> 13.1 14.34 1 54 0 1
#> 90.1 20.94 1 50 0 1
#> 40 18.00 1 28 1 0
#> 168.1 23.72 1 70 0 0
#> 29.1 15.45 1 68 1 0
#> 179 18.63 1 42 0 0
#> 168.2 23.72 1 70 0 0
#> 99.1 21.19 1 38 0 1
#> 37 12.52 1 57 1 0
#> 99.2 21.19 1 38 0 1
#> 52 10.42 1 52 0 1
#> 194.3 22.40 1 38 0 1
#> 150.1 20.33 1 48 0 0
#> 166 19.98 1 48 0 0
#> 79 16.23 1 54 1 0
#> 177.1 12.53 1 75 0 0
#> 90.2 20.94 1 50 0 1
#> 15 22.68 1 48 0 0
#> 145 10.07 1 65 1 0
#> 154 12.63 1 20 1 0
#> 168.3 23.72 1 70 0 0
#> 169.2 22.41 1 46 0 0
#> 150.2 20.33 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 154.1 12.63 1 20 1 0
#> 125.1 15.65 1 67 1 0
#> 125.2 15.65 1 67 1 0
#> 110 17.56 1 65 0 1
#> 43.3 12.10 1 61 0 1
#> 169.3 22.41 1 46 0 0
#> 127.1 3.53 1 62 0 1
#> 129.1 23.41 1 53 1 0
#> 141 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 33 24.00 0 53 0 0
#> 173 24.00 0 19 0 1
#> 104 24.00 0 50 1 0
#> 54 24.00 0 53 1 0
#> 74 24.00 0 43 0 1
#> 83 24.00 0 6 0 0
#> 142 24.00 0 53 0 0
#> 3 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 75 24.00 0 21 1 0
#> 163 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 19 24.00 0 57 0 1
#> 162 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 17 24.00 0 38 0 1
#> 73 24.00 0 NA 0 1
#> 138 24.00 0 44 1 0
#> 75.1 24.00 0 21 1 0
#> 191 24.00 0 60 0 1
#> 62 24.00 0 71 0 0
#> 48 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 64 24.00 0 43 0 0
#> 38 24.00 0 31 1 0
#> 119.1 24.00 0 17 0 0
#> 54.1 24.00 0 53 1 0
#> 161 24.00 0 45 0 0
#> 182 24.00 0 35 0 0
#> 21 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 11 24.00 0 42 0 1
#> 103 24.00 0 56 1 0
#> 62.1 24.00 0 71 0 0
#> 116 24.00 0 58 0 1
#> 185 24.00 0 44 1 0
#> 19.1 24.00 0 57 0 1
#> 34 24.00 0 36 0 0
#> 115 24.00 0 NA 1 0
#> 144 24.00 0 28 0 1
#> 131 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 83.1 24.00 0 6 0 0
#> 84 24.00 0 39 0 1
#> 47 24.00 0 38 0 1
#> 84.1 24.00 0 39 0 1
#> 191.1 24.00 0 60 0 1
#> 182.1 24.00 0 35 0 0
#> 144.1 24.00 0 28 0 1
#> 11.1 24.00 0 42 0 1
#> 160.1 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 118 24.00 0 44 1 0
#> 198.1 24.00 0 66 0 1
#> 7 24.00 0 37 1 0
#> 146 24.00 0 63 1 0
#> 138.1 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 162.1 24.00 0 51 0 0
#> 126.1 24.00 0 48 0 0
#> 62.2 24.00 0 71 0 0
#> 103.1 24.00 0 56 1 0
#> 178.1 24.00 0 52 1 0
#> 46 24.00 0 71 0 0
#> 161.1 24.00 0 45 0 0
#> 115.1 24.00 0 NA 1 0
#> 186 24.00 0 45 1 0
#> 74.1 24.00 0 43 0 1
#> 191.2 24.00 0 60 0 1
#> 185.1 24.00 0 44 1 0
#> 47.1 24.00 0 38 0 1
#> 44 24.00 0 56 0 0
#> 200.1 24.00 0 64 0 0
#> 121 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 147 24.00 0 76 1 0
#> 1 24.00 0 23 1 0
#> 31.1 24.00 0 36 0 1
#> 7.1 24.00 0 37 1 0
#> 80 24.00 0 41 0 0
#> 62.3 24.00 0 71 0 0
#> 28 24.00 0 67 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.820 NA NA NA
#> 2 age, Cure model 0.0201 NA NA NA
#> 3 grade_ii, Cure model -0.267 NA NA NA
#> 4 grade_iii, Cure model 0.323 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00177 NA NA NA
#> 2 grade_ii, Survival model 0.796 NA NA NA
#> 3 grade_iii, Survival model 0.718 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.82049 0.02007 -0.26720 0.32277
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 249.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.82049124 0.02007463 -0.26720408 0.32276606
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001772883 0.796146239 0.717790374
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.57787986 0.49697001 0.30839940 0.40757011 0.81267255 0.78655576
#> [7] 0.20868024 0.89951215 0.40757011 0.36199717 0.97877234 0.47655020
#> [13] 0.43089996 0.46553988 0.23041562 0.93421430 0.76652420 0.66106982
#> [19] 0.79322259 0.63693460 0.88749087 0.97877234 0.30839940 0.96240420
#> [25] 0.81916680 0.56050025 0.09126687 0.88749087 0.84469342 0.45413051
#> [31] 0.89951215 0.62857295 0.71566961 0.12452198 0.66106982 0.94564070
#> [37] 0.70817020 0.36199717 0.27913951 0.74521202 0.56050025 0.58648206
#> [43] 0.73793218 0.43089996 0.72315739 0.82565558 0.03583547 0.73054905
#> [49] 0.80617478 0.92260681 0.52522815 0.47655020 0.55171978 0.03583547
#> [55] 0.26336567 0.36199717 0.98945949 0.96792523 0.75240391 0.83833289
#> [61] 0.63693460 0.96792523 0.67709506 0.61181461 0.89951215 0.95683535
#> [67] 0.94564070 0.84469342 0.68504245 0.86929060 0.82565558 0.52522815
#> [73] 0.69286507 0.12452198 0.79322259 0.65299656 0.12452198 0.49697001
#> [79] 0.88145053 0.49697001 0.92843319 0.36199717 0.58648206 0.62019881
#> [85] 0.75951129 0.86929060 0.52522815 0.29380173 0.93995333 0.85710644
#> [91] 0.12452198 0.30839940 0.58648206 0.85710644 0.76652420 0.76652420
#> [97] 0.70057197 0.89951215 0.30839940 0.98945949 0.23041562 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 128 99 169 66 180 39 164 43 66.1 194 149 153 175
#> 20.35 21.19 22.41 22.13 14.82 15.59 23.60 12.10 22.13 22.40 8.37 21.33 21.91
#> 139 129 61 125 8 29 55 56 149.1 169.1 183 133 68
#> 21.49 23.41 10.12 15.65 18.43 15.45 19.34 12.21 8.37 22.41 9.24 14.65 20.62
#> 78 56.1 123 136 43.1 105 30 168 8.1 101 111 194.1 63
#> 23.88 12.21 13.00 21.83 12.10 19.75 17.43 23.72 18.43 9.97 17.45 22.40 22.77
#> 130 68.1 150 106 175.1 45 13 24 23 157 10 90 153.1
#> 16.47 20.62 20.33 16.67 21.91 17.42 14.34 23.89 16.92 15.10 10.53 20.94 21.33
#> 32 24.1 92 194.2 127 16 5 155 55.1 16.1 108 158 43.2
#> 20.90 23.89 22.92 22.40 3.53 8.71 16.43 13.08 19.34 8.71 18.29 20.14 12.10
#> 187 101.1 123.1 51 177 13.1 90.1 40 168.1 29.1 179 168.2 99.1
#> 9.92 9.97 13.00 18.23 12.53 14.34 20.94 18.00 23.72 15.45 18.63 23.72 21.19
#> 37 99.2 52 194.3 150.1 166 79 177.1 90.2 15 145 154 168.3
#> 12.52 21.19 10.42 22.40 20.33 19.98 16.23 12.53 20.94 22.68 10.07 12.63 23.72
#> 169.2 150.2 154.1 125.1 125.2 110 43.3 169.3 127.1 129.1 141 126 9
#> 22.41 20.33 12.63 15.65 15.65 17.56 12.10 22.41 3.53 23.41 24.00 24.00 24.00
#> 160 31 33 173 104 54 74 83 142 3 12 75 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 109 19 162 200 17 138 75.1 191 62 48 119 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 119.1 54.1 161 182 21 94 11 103 62.1 116 185 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 144 131 20 83.1 84 47 84.1 191.1 182.1 144.1 11.1 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 118 198.1 7 146 138.1 53 162.1 126.1 62.2 103.1 178.1 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 186 74.1 191.2 185.1 47.1 44 200.1 121 35 147 1 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.1 80 62.3 28
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[99]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002822241 0.690773262 0.489722692
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.64646811 0.01174006 0.43376859
#> grade_iii, Cure model
#> 0.39550725
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 40 18.00 1 28 1 0
#> 37 12.52 1 57 1 0
#> 85 16.44 1 36 0 0
#> 114 13.68 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 136 21.83 1 43 0 1
#> 8 18.43 1 32 0 0
#> 187 9.92 1 39 1 0
#> 57 14.46 1 45 0 1
#> 37.1 12.52 1 57 1 0
#> 52 10.42 1 52 0 1
#> 37.2 12.52 1 57 1 0
#> 194 22.40 1 38 0 1
#> 167 15.55 1 56 1 0
#> 96 14.54 1 33 0 1
#> 24 23.89 1 38 0 0
#> 60 13.15 1 38 1 0
#> 13 14.34 1 54 0 1
#> 76 19.22 1 54 0 1
#> 105 19.75 1 60 0 0
#> 110 17.56 1 65 0 1
#> 111 17.45 1 47 0 1
#> 99 21.19 1 38 0 1
#> 93 10.33 1 52 0 1
#> 16 8.71 1 71 0 1
#> 16.1 8.71 1 71 0 1
#> 101 9.97 1 10 0 1
#> 78 23.88 1 43 0 0
#> 123 13.00 1 44 1 0
#> 10 10.53 1 34 0 0
#> 188 16.16 1 46 0 1
#> 184 17.77 1 38 0 0
#> 100 16.07 1 60 0 0
#> 111.1 17.45 1 47 0 1
#> 52.1 10.42 1 52 0 1
#> 111.2 17.45 1 47 0 1
#> 158 20.14 1 74 1 0
#> 10.1 10.53 1 34 0 0
#> 177 12.53 1 75 0 0
#> 140 12.68 1 59 1 0
#> 92 22.92 1 47 0 1
#> 197 21.60 1 69 1 0
#> 101.1 9.97 1 10 0 1
#> 93.1 10.33 1 52 0 1
#> 39 15.59 1 37 0 1
#> 100.1 16.07 1 60 0 0
#> 158.1 20.14 1 74 1 0
#> 52.2 10.42 1 52 0 1
#> 63 22.77 1 31 1 0
#> 23 16.92 1 61 0 0
#> 60.1 13.15 1 38 1 0
#> 159 10.55 1 50 0 1
#> 69 23.23 1 25 0 1
#> 59 10.16 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 123.1 13.00 1 44 1 0
#> 199 19.81 1 NA 0 1
#> 189 10.51 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 113 22.86 1 34 0 0
#> 187.1 9.92 1 39 1 0
#> 139 21.49 1 63 1 0
#> 106 16.67 1 49 1 0
#> 136.1 21.83 1 43 0 1
#> 59.1 10.16 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 145 10.07 1 65 1 0
#> 145.1 10.07 1 65 1 0
#> 134 17.81 1 47 1 0
#> 170.1 19.54 1 43 0 1
#> 145.2 10.07 1 65 1 0
#> 5 16.43 1 51 0 1
#> 56 12.21 1 60 0 0
#> 6 15.64 1 39 0 0
#> 58 19.34 1 39 0 0
#> 179 18.63 1 42 0 0
#> 184.1 17.77 1 38 0 0
#> 78.1 23.88 1 43 0 0
#> 159.1 10.55 1 50 0 1
#> 129 23.41 1 53 1 0
#> 136.2 21.83 1 43 0 1
#> 114.1 13.68 1 NA 0 0
#> 45 17.42 1 54 0 1
#> 153 21.33 1 55 1 0
#> 15 22.68 1 48 0 0
#> 140.1 12.68 1 59 1 0
#> 124 9.73 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 145.3 10.07 1 65 1 0
#> 197.1 21.60 1 69 1 0
#> 63.1 22.77 1 31 1 0
#> 78.2 23.88 1 43 0 0
#> 76.1 19.22 1 54 0 1
#> 10.2 10.53 1 34 0 0
#> 8.1 18.43 1 32 0 0
#> 168 23.72 1 70 0 0
#> 86 23.81 1 58 0 1
#> 30 17.43 1 78 0 0
#> 168.1 23.72 1 70 0 0
#> 4 17.64 1 NA 0 1
#> 157 15.10 1 47 0 0
#> 86.1 23.81 1 58 0 1
#> 18 15.21 1 49 1 0
#> 97 19.14 1 65 0 1
#> 43 12.10 1 61 0 1
#> 50 10.02 1 NA 1 0
#> 15.1 22.68 1 48 0 0
#> 180 14.82 1 37 0 0
#> 194.1 22.40 1 38 0 1
#> 107 11.18 1 54 1 0
#> 93.2 10.33 1 52 0 1
#> 37.3 12.52 1 57 1 0
#> 182 24.00 0 35 0 0
#> 87 24.00 0 27 0 0
#> 83 24.00 0 6 0 0
#> 193 24.00 0 45 0 1
#> 176 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 118 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 64 24.00 0 43 0 0
#> 22 24.00 0 52 1 0
#> 173 24.00 0 19 0 1
#> 116 24.00 0 58 0 1
#> 138 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 163 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 72 24.00 0 40 0 1
#> 120 24.00 0 68 0 1
#> 17.1 24.00 0 38 0 1
#> 64.1 24.00 0 43 0 0
#> 17.2 24.00 0 38 0 1
#> 84 24.00 0 39 0 1
#> 74 24.00 0 43 0 1
#> 35 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 191 24.00 0 60 0 1
#> 95 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 62 24.00 0 71 0 0
#> 148 24.00 0 61 1 0
#> 172.1 24.00 0 41 0 0
#> 35.1 24.00 0 51 0 0
#> 132.1 24.00 0 55 0 0
#> 21 24.00 0 47 0 0
#> 2 24.00 0 9 0 0
#> 122 24.00 0 66 0 0
#> 131 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 84.1 24.00 0 39 0 1
#> 115 24.00 0 NA 1 0
#> 47 24.00 0 38 0 1
#> 112 24.00 0 61 0 0
#> 19 24.00 0 57 0 1
#> 121 24.00 0 57 1 0
#> 87.1 24.00 0 27 0 0
#> 20.1 24.00 0 46 1 0
#> 35.2 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 165.1 24.00 0 47 0 0
#> 193.1 24.00 0 45 0 1
#> 165.2 24.00 0 47 0 0
#> 73 24.00 0 NA 0 1
#> 120.1 24.00 0 68 0 1
#> 11 24.00 0 42 0 1
#> 83.1 24.00 0 6 0 0
#> 178 24.00 0 52 1 0
#> 116.1 24.00 0 58 0 1
#> 200 24.00 0 64 0 0
#> 186 24.00 0 45 1 0
#> 172.2 24.00 0 41 0 0
#> 67.1 24.00 0 25 0 0
#> 95.1 24.00 0 68 0 1
#> 22.1 24.00 0 52 1 0
#> 11.1 24.00 0 42 0 1
#> 148.1 24.00 0 61 1 0
#> 137 24.00 0 45 1 0
#> 35.3 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 65 24.00 0 57 1 0
#> 27 24.00 0 63 1 0
#> 80 24.00 0 41 0 0
#> 182.1 24.00 0 35 0 0
#> 19.1 24.00 0 57 0 1
#> 152 24.00 0 36 0 1
#> 198 24.00 0 66 0 1
#> 186.1 24.00 0 45 1 0
#> 198.1 24.00 0 66 0 1
#> 118.1 24.00 0 44 1 0
#> 165.3 24.00 0 47 0 0
#> 137.1 24.00 0 45 1 0
#> 191.1 24.00 0 60 0 1
#> 151 24.00 0 42 0 0
#> 161 24.00 0 45 0 0
#> 7 24.00 0 37 1 0
#> 53 24.00 0 32 0 1
#> 95.2 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.646 NA NA NA
#> 2 age, Cure model 0.0117 NA NA NA
#> 3 grade_ii, Cure model 0.434 NA NA NA
#> 4 grade_iii, Cure model 0.396 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00282 NA NA NA
#> 2 grade_ii, Survival model 0.691 NA NA NA
#> 3 grade_iii, Survival model 0.490 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.64647 0.01174 0.43377 0.39551
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 256.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.64646811 0.01174006 0.43376859 0.39550725
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002822241 0.690773262 0.489722692
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.58165929 0.83729186 0.67637128 0.36739243 0.38016836 0.56480530
#> [7] 0.97824770 0.77077791 0.83729186 0.91008042 0.83729186 0.34214581
#> [13] 0.73542533 0.76377407 0.03037077 0.78462238 0.77772789 0.53057385
#> [19] 0.49469250 0.61444285 0.62251234 0.45654587 0.92765581 0.98918328
#> [25] 0.98918328 0.96715999 0.07457356 0.80480844 0.89219776 0.69141817
#> [31] 0.59820641 0.69883610 0.62251234 0.91008042 0.62251234 0.47635788
#> [37] 0.89219776 0.83084072 0.81796507 0.25653938 0.41441510 0.96715999
#> [43] 0.92765581 0.72817116 0.69883610 0.47635788 0.91008042 0.28808410
#> [49] 0.66112085 0.78462238 0.88021153 0.23983245 0.50391453 0.80480844
#> [55] 0.71353595 0.27235759 0.97824770 0.43586635 0.66880218 0.38016836
#> [61] 0.79806362 0.94493984 0.94493984 0.59000700 0.50391453 0.94493984
#> [67] 0.68393132 0.86179686 0.72085788 0.52164817 0.55629030 0.59820641
#> [73] 0.07457356 0.88021153 0.22220400 0.38016836 0.65342271 0.44636537
#> [79] 0.31528223 0.81796507 0.46654432 0.94493984 0.41441510 0.28808410
#> [85] 0.07457356 0.53057385 0.89219776 0.56480530 0.18458124 0.14524325
#> [91] 0.64564203 0.18458124 0.74965679 0.14524325 0.74258508 0.54775887
#> [97] 0.86798134 0.31528223 0.75671905 0.34214581 0.87412475 0.92765581
#> [103] 0.83729186 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 40 37 85 66 136 8 187 57 37.1 52 37.2 194 167
#> 18.00 12.52 16.44 22.13 21.83 18.43 9.92 14.46 12.52 10.42 12.52 22.40 15.55
#> 96 24 60 13 76 105 110 111 99 93 16 16.1 101
#> 14.54 23.89 13.15 14.34 19.22 19.75 17.56 17.45 21.19 10.33 8.71 8.71 9.97
#> 78 123 10 188 184 100 111.1 52.1 111.2 158 10.1 177 140
#> 23.88 13.00 10.53 16.16 17.77 16.07 17.45 10.42 17.45 20.14 10.53 12.53 12.68
#> 92 197 101.1 93.1 39 100.1 158.1 52.2 63 23 60.1 159 69
#> 22.92 21.60 9.97 10.33 15.59 16.07 20.14 10.42 22.77 16.92 13.15 10.55 23.23
#> 170 123.1 26 113 187.1 139 106 136.1 155 145 145.1 134 170.1
#> 19.54 13.00 15.77 22.86 9.92 21.49 16.67 21.83 13.08 10.07 10.07 17.81 19.54
#> 145.2 5 56 6 58 179 184.1 78.1 159.1 129 136.2 45 153
#> 10.07 16.43 12.21 15.64 19.34 18.63 17.77 23.88 10.55 23.41 21.83 17.42 21.33
#> 15 140.1 90 145.3 197.1 63.1 78.2 76.1 10.2 8.1 168 86 30
#> 22.68 12.68 20.94 10.07 21.60 22.77 23.88 19.22 10.53 18.43 23.72 23.81 17.43
#> 168.1 157 86.1 18 97 43 15.1 180 194.1 107 93.2 37.3 182
#> 23.72 15.10 23.81 15.21 19.14 12.10 22.68 14.82 22.40 11.18 10.33 12.52 24.00
#> 87 83 193 176 172 118 17 64 22 173 116 138 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 67 72 120 17.1 64.1 17.2 84 74 35 28 191 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 62 148 172.1 35.1 132.1 21 2 122 131 165 48 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84.1 47 112 19 121 87.1 20.1 35.2 38 165.1 193.1 165.2 120.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 83.1 178 116.1 200 186 172.2 67.1 95.1 22.1 11.1 148.1 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.3 144 65 27 80 182.1 19.1 152 198 186.1 198.1 118.1 165.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 191.1 151 161 7 53 95.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[100]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.009279244 0.213381555 0.493055301
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.21415549 0.02171483 0.23061292
#> grade_iii, Cure model
#> 1.13045238
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55c023d25ae8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 23 16.92 1 61 0 0
#> 18 15.21 1 49 1 0
#> 61 10.12 1 36 0 1
#> 50 10.02 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 177 12.53 1 75 0 0
#> 130 16.47 1 53 0 1
#> 78 23.88 1 43 0 0
#> 111 17.45 1 47 0 1
#> 108 18.29 1 39 0 1
#> 14 12.89 1 21 0 0
#> 24 23.89 1 38 0 0
#> 77 7.27 1 67 0 1
#> 134 17.81 1 47 1 0
#> 129 23.41 1 53 1 0
#> 26 15.77 1 49 0 1
#> 86 23.81 1 58 0 1
#> 93 10.33 1 52 0 1
#> 89 11.44 1 NA 0 0
#> 57 14.46 1 45 0 1
#> 91 5.33 1 61 0 1
#> 51 18.23 1 83 0 1
#> 40 18.00 1 28 1 0
#> 129.1 23.41 1 53 1 0
#> 18.1 15.21 1 49 1 0
#> 26.1 15.77 1 49 0 1
#> 76 19.22 1 54 0 1
#> 25 6.32 1 34 1 0
#> 158 20.14 1 74 1 0
#> 16 8.71 1 71 0 1
#> 51.1 18.23 1 83 0 1
#> 153 21.33 1 55 1 0
#> 127 3.53 1 62 0 1
#> 16.1 8.71 1 71 0 1
#> 85 16.44 1 36 0 0
#> 168 23.72 1 70 0 0
#> 139 21.49 1 63 1 0
#> 129.2 23.41 1 53 1 0
#> 139.1 21.49 1 63 1 0
#> 78.1 23.88 1 43 0 0
#> 39 15.59 1 37 0 1
#> 107 11.18 1 54 1 0
#> 79 16.23 1 54 1 0
#> 88 18.37 1 47 0 0
#> 140 12.68 1 59 1 0
#> 140.1 12.68 1 59 1 0
#> 49 12.19 1 48 1 0
#> 66 22.13 1 53 0 0
#> 60 13.15 1 38 1 0
#> 183 9.24 1 67 1 0
#> 110 17.56 1 65 0 1
#> 39.1 15.59 1 37 0 1
#> 105 19.75 1 60 0 0
#> 58 19.34 1 39 0 0
#> 108.1 18.29 1 39 0 1
#> 29 15.45 1 68 1 0
#> 180 14.82 1 37 0 0
#> 30 17.43 1 78 0 0
#> 166 19.98 1 48 0 0
#> 184 17.77 1 38 0 0
#> 106 16.67 1 49 1 0
#> 181 16.46 1 45 0 1
#> 188 16.16 1 46 0 1
#> 197 21.60 1 69 1 0
#> 69 23.23 1 25 0 1
#> 96 14.54 1 33 0 1
#> 4 17.64 1 NA 0 1
#> 6.1 15.64 1 39 0 0
#> 89.1 11.44 1 NA 0 0
#> 43 12.10 1 61 0 1
#> 100 16.07 1 60 0 0
#> 13 14.34 1 54 0 1
#> 51.2 18.23 1 83 0 1
#> 14.1 12.89 1 21 0 0
#> 39.2 15.59 1 37 0 1
#> 136 21.83 1 43 0 1
#> 43.1 12.10 1 61 0 1
#> 100.1 16.07 1 60 0 0
#> 130.1 16.47 1 53 0 1
#> 128 20.35 1 35 0 1
#> 97 19.14 1 65 0 1
#> 175 21.91 1 43 0 0
#> 183.1 9.24 1 67 1 0
#> 100.2 16.07 1 60 0 0
#> 179 18.63 1 42 0 0
#> 111.1 17.45 1 47 0 1
#> 10 10.53 1 34 0 0
#> 111.2 17.45 1 47 0 1
#> 145 10.07 1 65 1 0
#> 190 20.81 1 42 1 0
#> 93.1 10.33 1 52 0 1
#> 133 14.65 1 57 0 0
#> 77.1 7.27 1 67 0 1
#> 117 17.46 1 26 0 1
#> 96.1 14.54 1 33 0 1
#> 117.1 17.46 1 26 0 1
#> 58.1 19.34 1 39 0 0
#> 10.1 10.53 1 34 0 0
#> 127.1 3.53 1 62 0 1
#> 187 9.92 1 39 1 0
#> 58.2 19.34 1 39 0 0
#> 133.1 14.65 1 57 0 0
#> 88.1 18.37 1 47 0 0
#> 69.1 23.23 1 25 0 1
#> 192 16.44 1 31 1 0
#> 145.1 10.07 1 65 1 0
#> 26.2 15.77 1 49 0 1
#> 69.2 23.23 1 25 0 1
#> 188.1 16.16 1 46 0 1
#> 190.1 20.81 1 42 1 0
#> 56 12.21 1 60 0 0
#> 127.2 3.53 1 62 0 1
#> 95 24.00 0 68 0 1
#> 12 24.00 0 63 0 0
#> 7 24.00 0 37 1 0
#> 122 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 22 24.00 0 52 1 0
#> 115 24.00 0 NA 1 0
#> 64 24.00 0 43 0 0
#> 144 24.00 0 28 0 1
#> 148 24.00 0 61 1 0
#> 156 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 176 24.00 0 43 0 1
#> 33 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 131 24.00 0 66 0 0
#> 119 24.00 0 17 0 0
#> 115.1 24.00 0 NA 1 0
#> 141 24.00 0 44 1 0
#> 7.1 24.00 0 37 1 0
#> 196 24.00 0 19 0 0
#> 19 24.00 0 57 0 1
#> 116 24.00 0 58 0 1
#> 137 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 162 24.00 0 51 0 0
#> 12.1 24.00 0 63 0 0
#> 67 24.00 0 25 0 0
#> 121 24.00 0 57 1 0
#> 115.2 24.00 0 NA 1 0
#> 31 24.00 0 36 0 1
#> 198 24.00 0 66 0 1
#> 196.1 24.00 0 19 0 0
#> 64.1 24.00 0 43 0 0
#> 143 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 186 24.00 0 45 1 0
#> 142 24.00 0 53 0 0
#> 47 24.00 0 38 0 1
#> 121.1 24.00 0 57 1 0
#> 44 24.00 0 56 0 0
#> 65 24.00 0 57 1 0
#> 178.1 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 35 24.00 0 51 0 0
#> 196.2 24.00 0 19 0 0
#> 74 24.00 0 43 0 1
#> 83 24.00 0 6 0 0
#> 138 24.00 0 44 1 0
#> 95.1 24.00 0 68 0 1
#> 109 24.00 0 48 0 0
#> 146 24.00 0 63 1 0
#> 2 24.00 0 9 0 0
#> 46 24.00 0 71 0 0
#> 98 24.00 0 34 1 0
#> 67.1 24.00 0 25 0 0
#> 146.1 24.00 0 63 1 0
#> 146.2 24.00 0 63 1 0
#> 33.1 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 143.1 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 162.1 24.00 0 51 0 0
#> 72.1 24.00 0 40 0 1
#> 109.1 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 44.1 24.00 0 56 0 0
#> 182 24.00 0 35 0 0
#> 137.1 24.00 0 45 1 0
#> 67.2 24.00 0 25 0 0
#> 144.1 24.00 0 28 0 1
#> 11 24.00 0 42 0 1
#> 73 24.00 0 NA 0 1
#> 87 24.00 0 27 0 0
#> 142.1 24.00 0 53 0 0
#> 144.2 24.00 0 28 0 1
#> 87.1 24.00 0 27 0 0
#> 95.2 24.00 0 68 0 1
#> 54 24.00 0 53 1 0
#> 67.3 24.00 0 25 0 0
#> 20 24.00 0 46 1 0
#> 109.2 24.00 0 48 0 0
#> 135 24.00 0 58 1 0
#> 71 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 144.3 24.00 0 28 0 1
#> 112 24.00 0 61 0 0
#> 151 24.00 0 42 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.21 NA NA NA
#> 2 age, Cure model 0.0217 NA NA NA
#> 3 grade_ii, Cure model 0.231 NA NA NA
#> 4 grade_iii, Cure model 1.13 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00928 NA NA NA
#> 2 grade_ii, Survival model 0.213 NA NA NA
#> 3 grade_iii, Survival model 0.493 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.21416 0.02171 0.23061 1.13045
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 263.2
#> Residual Deviance: 247.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.21415549 0.02171483 0.23061292 1.13045238
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.009279244 0.213381555 0.493055301
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.67721730 0.80959019 0.93249685 0.77599305 0.88338344 0.69064422
#> [7] 0.11805692 0.65002065 0.56512228 0.86290577 0.05845847 0.96954455
#> [13] 0.61303676 0.23834158 0.75878509 0.18592706 0.92294537 0.84725575
#> [19] 0.98282919 0.58230559 0.60532438 0.23834158 0.80959019 0.75878509
#> [25] 0.51911452 0.97840359 0.45882547 0.96051650 0.58230559 0.41409662
#> [31] 0.98721756 0.96051650 0.70991197 0.21359643 0.39026762 0.23834158
#> [37] 0.39026762 0.11805692 0.78743383 0.90833650 0.72250502 0.54720282
#> [43] 0.87321304 0.87321304 0.89350295 0.33408235 0.85772329 0.95130100
#> [49] 0.62824666 0.78743383 0.47969861 0.48990568 0.56512228 0.80406030
#> [55] 0.82047140 0.67042099 0.46932714 0.62066140 0.68396207 0.70352771
#> [61] 0.72877201 0.37717428 0.29036350 0.83666881 0.77599305 0.89852550
#> [67] 0.74093772 0.85251687 0.58230559 0.86290577 0.78743383 0.36343819
#> [73] 0.89852550 0.74093772 0.69064422 0.44796083 0.52872651 0.34891157
#> [79] 0.95130100 0.74093772 0.53800246 0.65002065 0.91322770 0.65002065
#> [85] 0.93725345 0.42582399 0.92294537 0.82591532 0.96954455 0.63565370
#> [91] 0.83666881 0.63565370 0.48990568 0.91322770 0.98721756 0.94662275
#> [97] 0.48990568 0.82591532 0.54720282 0.29036350 0.70991197 0.93725345
#> [103] 0.75878509 0.29036350 0.72877201 0.42582399 0.88845393 0.98721756
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 23 18 61 6 177 130 78 111 108 14 24 77 134
#> 16.92 15.21 10.12 15.64 12.53 16.47 23.88 17.45 18.29 12.89 23.89 7.27 17.81
#> 129 26 86 93 57 91 51 40 129.1 18.1 26.1 76 25
#> 23.41 15.77 23.81 10.33 14.46 5.33 18.23 18.00 23.41 15.21 15.77 19.22 6.32
#> 158 16 51.1 153 127 16.1 85 168 139 129.2 139.1 78.1 39
#> 20.14 8.71 18.23 21.33 3.53 8.71 16.44 23.72 21.49 23.41 21.49 23.88 15.59
#> 107 79 88 140 140.1 49 66 60 183 110 39.1 105 58
#> 11.18 16.23 18.37 12.68 12.68 12.19 22.13 13.15 9.24 17.56 15.59 19.75 19.34
#> 108.1 29 180 30 166 184 106 181 188 197 69 96 6.1
#> 18.29 15.45 14.82 17.43 19.98 17.77 16.67 16.46 16.16 21.60 23.23 14.54 15.64
#> 43 100 13 51.2 14.1 39.2 136 43.1 100.1 130.1 128 97 175
#> 12.10 16.07 14.34 18.23 12.89 15.59 21.83 12.10 16.07 16.47 20.35 19.14 21.91
#> 183.1 100.2 179 111.1 10 111.2 145 190 93.1 133 77.1 117 96.1
#> 9.24 16.07 18.63 17.45 10.53 17.45 10.07 20.81 10.33 14.65 7.27 17.46 14.54
#> 117.1 58.1 10.1 127.1 187 58.2 133.1 88.1 69.1 192 145.1 26.2 69.2
#> 17.46 19.34 10.53 3.53 9.92 19.34 14.65 18.37 23.23 16.44 10.07 15.77 23.23
#> 188.1 190.1 56 127.2 95 12 7 122 132 22 64 144 148
#> 16.16 20.81 12.21 3.53 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 178 176 33 75 131 119 141 7.1 196 19 116 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 162 12.1 67 121 31 198 196.1 64.1 143 21 186 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 121.1 44 65 178.1 94 35 196.2 74 83 138 95.1 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 2 46 98 67.1 146.1 146.2 33.1 62 143.1 1 162.1 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.1 9 44.1 182 137.1 67.2 144.1 11 87 142.1 144.2 87.1 95.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 67.3 20 109.2 135 71 185 144.3 112 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 2
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>
#> $cure_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 0
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>